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2022· article· en· W6922636489 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsSoftmax functionValue (mathematics)Table (database)Pearson product-moment correlation coefficientConfusionCorrelationArtifact (error)

Abstract

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<p><b>Contains Supporting information Methods, Results, and Supporting information Tables A–I. Table A: Parameter recovery (schedule used for confirmation sample).</b> The table shows correlations (Pearson’s r) between simulated (“ground truth”) parameters (headers highlighted in grey) and the fitted (“recovered”) parameters (headers with white background) for the decision models of the initial (top) and later (bottom) searches. All parameters showed very good recovery (<i>r</i> > 0.88, diagonal, highlighted in blue). The off-diagonal values show that confusion between parameters was very low (all < 0.22). We used 500 simulated participants for these results. Data in files <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s019" target="_blank">S13</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s020" target="_blank">S14</a> Data. <b>Table B: Parameter correlations for initial decisions</b> (confirmation sample). We ran a Pearson correlation of the hierarchically fit parameter estimates from our cognitive model on the initial decisions to look at their relationships. Even though simulations (S1 Table) showed very low parameter confusions, parameters from real participants showed in parts substantial correlations (Pearson’s r), suggesting those correlations are a real relationship existing in participants, rather than an artifact of model fitting. invTemp (inverse temperature of the softmax equation linking value to choice probabilities), SearchBias (bias for or against searching). Prospective (prospective value of the model), Myopic (Myopic value of the model). AvgProspVChange (average change of prospective value per search in the future). Data in file <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s017" target="_blank">S11 Data</a>. <b>Table C: Parameter correlations for later searches</b> (confirmation sample). We ran a Pearson correlation of the hierarchically fit parameter estimates from our cognitive model on the later decisions to look at their relationships. Even though simulations (S1 Table) showed very low parameter confusions, parameters from real participants showed in parts substantial correlations (Pearson’s r), suggesting those correlations are a real relationship existing in participants, rather than an artifact of model fitting. Abbreviations same as S2 Table. ProspVS1 (prospective value at first search). ProspVS1mAdapted (change of prospective value since first search). PrevSearches (number of previous searches). Total Cost (sum of total cost since first search). Data in file <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s015" target="_blank">S9 Data</a>. <b>Table D: Additional demographics (confirmation sample)</b>. Participants completed the following questionnaires. AMI [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref001" target="_blank">1</a>], OCI-R [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref002" target="_blank">2</a>], BDI [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref003" target="_blank">3</a>], Spielberger State Anxiety [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref004" target="_blank">4</a>], Liebowitz Social anxiety [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref005" target="_blank">5</a>], Short Scales for Measuring Schizotypy [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref006" target="_blank">6</a>] (“unusual experiences” and “introvertive anhedonia” subscale), Fatigue scale [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref007" target="_blank">7</a>], and Toronto alexithymia scale [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.ref008" target="_blank">8</a>]. Depression cutoffs were (less than 13 “Minimal,” less then 20 “Mild,” less than 29 “Moderate,” and higher or equal 29 “Severe”). Obsessive compulsion less than 21 “none,” otherwise “clinically significant”). For social anxiety, we had less than 30 as “none,” between 30 but less than 60 as “possible” and at and above 60 as “probable” social anxiety. For Alexithymia, we had less than 52 as none, between 52 but less than 61 as “possible” and at and above 62 as “present” Alexithymia. Fatigue was “none” below 22, “present” between 22 and 34, and “extreme” above 34. Data in file <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s011" target="_blank">S5 Data</a>. <b>Table E: Results of regressions linking clinical dimensions to decision and self-report measures controlling for medication status</b> (confirmation sample). As control regressors, we included age, gender and education (as in main manuscript). Additionally, here, psychoactive medication status is also included (coded as “Yes”/“No” as there were too few respondents of individual types of medications). Data in files <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s008" target="_blank">S2</a>, <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s012" target="_blank">S6</a>, <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s015" target="_blank">S9</a>, and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s022" target="_blank">S16 Data</a>. <b>Table F: Results of regressions linking clinical dimensions to later search decisions.</b> Results of all parameters from model fit to the later search decisions and dimensions. We used 90% 2-sided CIs, to show the results of 1-sided (95% CI) tests for our preregistered hypotheses and to show what other links have any evidence. Data in files S9 and 16 Data. <b>Table G: Results of regressions linking clinical dimensions to initial search decisions.</b> Results of all parameters from model fit to the initial search decisions and dimensions. We used 90% 2-sided CIs, to show the results of 1-sided tests for our preregistered hypotheses and to show what other links have any evidence. Data in files <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s017" target="_blank">S11</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s022" target="_blank">S16</a> Data. <b>Table H: Results of regressions linking clinical dimensions to self-report measures.</b> Results of all self-report measures fit to the dimensions. We used 90% 2-sided CI, to show the results of 1-sided tests for our preregistered hypotheses and to show what other links have any evidence. Data in files <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s008" target="_blank">S2</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s022" target="_blank">S16</a> Data. <b>Table I: Additional medication information (confirmation sample)</b>. All information for the types of medications excluded and included participants used (No and Yes). The most common medication were selective serotonin reuptake inhibitor. Data in file <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3001566#pbio.3001566.s012" target="_blank">S6 Data</a>. AMI, Apathy Motivation Index; BDI, Beck Depression Inventory; CI, confidence interval; OCI-R, Obsessive-Compulsive Inventory.</p> <p>(PDF)</p>

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1630.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.228
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2022
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