{"id":"W4409064723","doi":"10.1037/pne0000360","title":"Memory for negative and positive emotional video clips.","year":2025,"lang":"en","type":"article","venue":"Psychology & Neuroscience","topic":"Memory Processes and Influences","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CLIPS; Psychology; Cognitive psychology; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005353617,0.0002723049,0.0001665141,0.0003191299,0.000363485,0.0009699761,0.0003690427,0.0003405298,0.00586637],"category_scores_gemma":[0.006707325,0.0001191442,0.0001238947,0.0001521797,0.0003049137,0.0008189229,0.0005121583,0.0005624841,0.0005503582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003621405,"about_ca_system_score_gemma":0.0003146893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002090603,"about_ca_topic_score_gemma":0.003074155,"domain_scores_codex":[0.9997703,0.00003658498,0.000008679292,0.00006274063,0.00008103098,0.00004064128],"domain_scores_gemma":[0.998629,0.0004693057,0.0003112905,0.0001321389,0.000235217,0.0002230454],"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":[0.01152999,0.001770312,0.1183158,0.0008365447,0.0004982068,0.001550786,0.007863067,0.0007341329,0.4920324,0.005885128,0.01771725,0.3412662],"study_design_scores_gemma":[0.000304975,0.003563468,0.9027405,0.0003687939,0.0005444838,0.002773696,0.004410587,0.002779436,0.06108581,0.009516778,0.01178509,0.000126289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551645,0.0008386442,0.001357617,0.0004301625,0.0003096997,0.00009135631,0.0003239471,0.00004060164,0.04144353],"genre_scores_gemma":[0.9907347,0.000552716,0.0006574784,0.0003281336,0.0001389787,0.00003399721,0.0003496228,0.00002308857,0.007181298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00586637,"threshold_uncertainty_score":0.01962501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04912407491413909,"score_gpt":0.3751075972798307,"score_spread":0.3259835223656916,"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."}}