{"id":"W2885315449","doi":"10.1111/cogs.12662","title":"Simple Co‐Occurrence Statistics Reproducibly Predict Association Ratings","year":2018,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Topic Modeling","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Deutsche Forschungsgemeinschaft","keywords":"Valence (chemistry); Word2vec; Psychology; Statistics; Co-occurrence; Natural language processing; Mathematics; Pattern recognition (psychology); Cognitive psychology; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0104834,0.0005816516,0.0006926259,0.001927787,0.000392296,0.002148193,0.0004494464,0.0008187964,0.002037573],"category_scores_gemma":[0.08977816,0.0003176296,0.0006324463,0.002006016,0.0008435079,0.00291875,0.0009875614,0.0007627397,0.0007531705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001965239,"about_ca_system_score_gemma":0.000261212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006026921,"about_ca_topic_score_gemma":0.001048859,"domain_scores_codex":[0.99163,0.003854073,0.000869979,0.001711574,0.001708678,0.0002256402],"domain_scores_gemma":[0.8146797,0.1535356,0.01311033,0.01134253,0.005423537,0.001908278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001512708,0.0002406618,0.8547909,0.0006200809,0.001210061,0.0002563532,0.002633449,0.006755525,0.03016222,0.002635852,0.001818082,0.09736421],"study_design_scores_gemma":[0.0000632958,0.0009882479,0.9093196,0.00005909717,0.0004199577,0.0009228798,0.001256872,0.06445746,0.0112084,0.008738725,0.002399832,0.0001656399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9505143,0.0004882356,0.04373598,0.0001265241,0.00005376478,0.00007862863,0.0006325039,0.0003139419,0.004056157],"genre_scores_gemma":[0.9907579,0.00008664599,0.00825197,0.00001926329,0.00002738779,0.00004663114,0.0004841975,0.00007072676,0.0002551877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0104834,"threshold_uncertainty_score":0.05544215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03476346330130259,"score_gpt":0.3255728526597379,"score_spread":0.2908093893584353,"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."}}