{"id":"W7133447372","doi":"","title":"Optimal testing situations for the automated analysis of cognitive components in natural language : a systematic literature review.","year":2025,"lang":"en","type":"preprint","venue":"ORBi UMONS","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Cognition; Natural language; Component (thermodynamics); Systematic review","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0164714,0.001591371,0.005772792,0.01264691,0.0007947213,0.004309302,0.002564215,0.00198852,0.004559618],"category_scores_gemma":[0.0768876,0.001090904,0.006150963,0.01093159,0.001306848,0.004194112,0.002261571,0.001428405,0.0005920087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004203411,"about_ca_system_score_gemma":0.02014523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008023098,"about_ca_topic_score_gemma":0.02580905,"domain_scores_codex":[0.9872431,0.0049532,0.004696065,0.0008751586,0.001982823,0.0002497911],"domain_scores_gemma":[0.9391156,0.049206,0.006453806,0.0008537633,0.004048395,0.0003224276],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0000990859,0.00002022498,0.0005375895,0.9013163,0.002455121,0.00006823173,0.0003736188,0.00009545669,0.000130336,0.0004604317,0.001440557,0.093003],"study_design_scores_gemma":[0.00009523351,0.0001212553,0.002309172,0.953796,0.01833093,0.0002925426,0.0005632638,0.00008375572,0.0001819873,0.000603899,0.02358304,0.00003883915],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006402864,0.9975014,0.0004298839,0.000293256,0.00008203656,0.0004786442,0.0003229467,0.00001073537,0.0002408206],"genre_scores_gemma":[0.01078806,0.9839444,0.002632786,0.0005787292,0.00006351827,0.001466122,0.0004088304,0.000009165121,0.0001084444],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9835286,"threshold_uncertainty_score":0.08711016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.309326438312249,"score_gpt":0.4852953835068626,"score_spread":0.1759689451946136,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}