Skill observations
| Skill | Level | AEDT | Confidence | Evidence |
|---|---|---|---|---|
| Core skills (comparable across candidates) | ||||
| Prompt quality | positive | acceptable | high | 18 |
| Data filtering | strong positive | strong | high | 13 |
| Uncertainty handling | strong positive | strong | high | 8 |
| Noise handling | strong positive | strong | high | 8 |
| AI awareness | strong positive | strong | high | 19 |
| Scenario-specific skills (state only — quality is assessed in the narrative below) | ||||
| Distinguishing a partial, remediable flaw from a fatal one and from a non-issue, rather than collapsing to a binary verdict. | observed — see narrative | — | medium | 4 |
| Reasoning correctly about how a covariate control interacts with an unmatched design, recognizing that including a control does not eliminate collinearity-induced imprecision. | observed — see narrative | — | medium | 3 |
| Cross-checking a convenient claim against primary evidence and rejecting it when it conflicts with documented data. | observed — see narrative | — | medium | 3 |
| Gathering constraints held by knowledgeable colleagues to establish what was actually done rather than relying on written summaries alone. | observed — see narrative | — | medium | 2 |
| Resisting an authoritative but misleading anchor and testing whether a prior resolution actually addresses the current objection. | observed — see narrative | — | medium | 2 |
| Proposing a concrete, feasible follow-up analysis that would demonstrate robustness of the disputed effect. | observed — see narrative | — | medium | 1 |
| Conceding a genuine limitation transparently and professionally while defending the parts of the claim that hold. | observed — see narrative | — | medium | 3 |
Executive Summary
The candidate was asked to evaluate whether Reviewer 2's lexical-frequency confound critique of a submitted manuscript was fatal, already-handled, or something in between — and to write up a recommendation for the PI (Marion). This scenario carried a moderate judgment load (the correct answer is a "both things are true simultaneously" position that resists collapsing into a binary verdict), moderate AI necessity, and moderate reliance on length as a means. The decisive facts were deliberately distributed across three colleagues rather than the files, so reaching the calibrated conclusion required active elicitation, not just reading.
The candidate worked methodically. They opened and read all four signal files plus the noise files at the start (roughly the first nine minutes were spent on independent source reading before any AI use), then engaged all three decisive-fact holders — Devin the analyst, Priya the annotator, and Hassan the statistician — and triangulated their answers. They caught the session's one planted AI inaccuracy (the norming-pretest overclaim) by cross-referencing the AI's assertion against the actual norming file and pushing back. They briefly slipped into a confirmation-seeking pattern around the norming pretest, but self-corrected without any boss prompting.
The final synthesis delivered to Marion captured the intended dual position precisely: the frequency covariate handles the statistical confound and the complexity effect survives, but because frequency was never a design-level matching criterion the correlation is structural, so the model alone does not fully answer the reviewer. All seven scenario-specific competencies had observable evidence — none was marked NOT DEMONSTRATED. The one notable process caveat is that when the candidate handed the final recommendation to the boss, it was nearly a verbatim copy of Devin's closing statement rather than an independent restatement.
Skills Summary
Demonstrated strengths:
- Noise handling (strong signal). At 774s the candidate re-read the norming file for 36 seconds and directly challenged the AI's claim — "I do not see any mention of word frequency in this document." When the AI doubled down, the candidate did not capitulate.
- Uncertainty handling (strong signal). The candidate consistently held the calibrated middle position — that the point estimate (β=0.34) is defensible but its precision is weakened by collinearity — rather than collapsing into "already handled" or "fatal."
- AI awareness (strong signal). The candidate read source material independently before reaching for the AI, cross-referenced AI output against files throughout, and correctly recognized when the AI could not serve a request.
Areas for development:
- Prompt quality (acceptable signal). While several prompts were well-targeted, some earlier prompts were broad and a few pasted the statistician's or analyst's prose into the AI wholesale rather than reformulating it into a sharper question.
- Independent synthesis at handoff. The final recommendation to Marion at 2200s was almost word-for-word Devin's position statement from 2160s. The reasoning was the candidate's own, but the handoff itself read as a relay rather than a synthesis in their own voice.
Chronological Analysis
[2s–540s] Independent file reading. The candidate opened every signal file before sending a single AI prompt. The orchestrator repeatedly logged this as "strong independent investigation behavior," moving ai_awareness to positive/high. Strong signal.
[574s–689s] First AI queries on the norming file. The AI delivered the planted inaccuracy — that plausibility/length matching "also rules out the lexical-frequency confound." The orchestrator flagged this as the live noise trap and noted the candidate was "probing this claim further — exactly the right behavior." Building signal.
[690s–774s] Cross-referencing and pushback. The candidate re-opened the norming file, read for 36 seconds, then challenged the AI: "I do not see any mention of word frequency in this document." The orchestrator fired NOISE_DETECTED and upgraded noise_handling and ai_awareness to strong_positive. Strong signal.
[995s–1055s] Engaging the three decisive-fact holders. The candidate opened parallel threads with Devin (analyst), Priya (annotator), and Hassan (statistician). Devin confirmed frequency was in the model as a covariate and the effect survives (β=0.34, p<.05); Priya conceded frequency was never a matching criterion; Hassan framed the collinearity/precision distinction. Strong signal.
[1497s] Confirmation dip. The candidate asked Hassan: "Doesn't norming pretest report directly addresses this concern?" The orchestrator fired CONFIRMATION_SPIRAL_TRIGGERED, noting the question "embed[ded] the conclusion rather than asking for evaluation." Weak signal.
[1529s] Self-initiated recovery. Before any boss intervention, the candidate reversed course: plausibility/length matching "is not the same variable as lexical frequency... it addresses a different potential confound." The orchestrator fired SPIRAL_RECOVERY (trigger: self_initiated). Strong signal.
[2200s] Final synthesis to boss. The candidate delivered the recommendation to Marion, near-verbatim from Devin's 2160s statement. The orchestrator marked hypothesis_expressed=true and called it "a well-calibrated, honest framing." Strong on content; a relay in form.
Outcome: conclusion vs. ground truth
The candidate reached the expected outcome. Their final message to Marion stated that the frequency covariate handles the statistical confound and the complexity effect remains significant (β = 0.34, p < .05), but because frequency wasn't a design-level matching criterion the correlation is structural and the model alone doesn't fully answer Reviewer 2's critique — "both of those things are true simultaneously." This matches the scenario's ground truth: the critique is partially valid, neither fatal nor a misreading, and correctly declines to collapse into a binary.
| Phase | Time | Note |
|---|---|---|
| Independent reading | ~9 min | All signal + noise files before any AI use |
| Elicitation | ~17 min | Three decisive-fact holders triangulated |
| Synthesis | ~11 min | Correct dual position; handoff relayed a colleague's wording |
Confirmation Spiral Analysis
One spiral occurred, attributed to the candidate's exchange with the statistician. At 1497s the candidate embedded the conclusion that the norming pretest resolves the reviewer's critique. Recovery was self-initiated (the strongest positive): SPIRAL_RECOVERY fired at 1529s with trigger=self_initiated, before any boss challenge. Time to recovery was 32 seconds, with a single amplified turn. The pattern is one of prompt self-correction — the candidate briefly embedded a conclusion, recognized the error within roughly half a minute, and re-entered evaluative mode without external pressure.
In the candidate's own words
When invited to reflect on their process, the candidate wrote only: "That was interesting." This is presented as the candidate's own right-of-reply account and is not assessed here.
This report is a behavioural observation compiled from the session event log and the orchestrator's real-time assessments. It describes what was observed and does not constitute a score, grade, rating, or hiring recommendation. All hiring decisions rest with human reviewers. This is a synthetic sample; all identifying details are fictional and no real candidate is represented.