{"id":"W4302030892","doi":"","title":"Pictures and words: Priming and category effects in object processing","year":2007,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Priming (agriculture); Object (grammar); Natural language processing; Computer science; Communication; Cognitive psychology; Psychology; Artificial intelligence; Linguistics; Biology; Philosophy","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":[0.001951124,0.0009788848,0.0008211718,0.0007517901,0.0005286714,0.001907267,0.001014169,0.002488274,0.01968534],"category_scores_gemma":[0.01565051,0.001266449,0.0004994581,0.0007816498,0.001443836,0.004356762,0.001933146,0.001984286,0.002091176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004881935,"about_ca_system_score_gemma":0.0007570693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007296486,"about_ca_topic_score_gemma":0.0006874924,"domain_scores_codex":[0.9990663,0.0003234055,0.00005412261,0.0002484166,0.0002253288,0.00008255728],"domain_scores_gemma":[0.9889065,0.008930298,0.0008245917,0.0004329295,0.0003282723,0.0005773168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01591076,0.0007132888,0.003703521,0.001485002,0.0001227523,0.0008501154,0.002414224,0.0003787367,0.8935925,0.02195794,0.001719939,0.05715131],"study_design_scores_gemma":[0.005711472,0.007658491,0.4371935,0.0005176151,0.001300182,0.01026623,0.002268601,0.009027191,0.2798606,0.2277405,0.01803322,0.0004223036],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530821,0.003933603,0.01264151,0.001157445,0.0009192881,0.000229218,0.0004382805,0.0002288838,0.02736973],"genre_scores_gemma":[0.9746484,0.002064121,0.01057867,0.001110911,0.0005988178,0.0004226857,0.0005327032,0.0004713102,0.009572482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01968534,"threshold_uncertainty_score":0.06585407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767248355666998,"score_gpt":0.2528174359760368,"score_spread":0.2351449524193669,"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."}}