{"id":"W2603793357","doi":"","title":"1st quarter comes to an end... : deal selection","year":2016,"lang":"en","type":"article","venue":"Without Prejudice","topic":"Competency Development and Evaluation","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Quarter (Canadian coin); Computer science; Artificial intelligence; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00349038,0.0002842075,0.0005054826,0.0007749131,0.006921443,0.007886136,0.0006463638,0.003179203,0.1559467],"category_scores_gemma":[0.01509281,0.0003224596,0.0003037737,0.0005386341,0.001389155,0.003741965,0.003762903,0.004146779,0.05180068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002390557,"about_ca_system_score_gemma":0.004099431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004987906,"about_ca_topic_score_gemma":0.01239028,"domain_scores_codex":[0.9975671,0.0005404792,0.00007460181,0.0002261282,0.0009671559,0.0006246619],"domain_scores_gemma":[0.9942119,0.0006578809,0.0003055891,0.000448218,0.001766956,0.002609531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00012463,0.0001949402,0.006073979,0.00003723942,0.000007704522,0.0002029977,0.001397144,0.00005039796,0.0005328843,0.02536599,0.8640651,0.1019471],"study_design_scores_gemma":[0.00002892897,0.0001735482,0.01757184,0.0001715431,0.00001125761,0.0003745901,0.006333265,0.0002965806,0.000876045,0.01609447,0.9580167,0.00005120133],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04843882,0.002105785,0.004388588,0.2154541,0.01344449,0.0001953551,0.0005119601,0.0008162294,0.7146446],"genre_scores_gemma":[0.1458089,0.0007454341,0.002110283,0.03739415,0.00248177,0.0001125387,0.0003572913,0.0004347664,0.8105549],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1559467,"threshold_uncertainty_score":0.5216935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03275195335477125,"score_gpt":0.3411437704023765,"score_spread":0.3083918170476052,"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."}}