{"id":"W3093773863","doi":"10.46290/cjok000004","title":"Pavlov’s Classical Conditioning","year":2020,"lang":"en","type":"article","venue":"Cascade Journal of Knowledge","topic":"Management and Marketing Education","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Classical conditioning; Conditioning; Field (mathematics); Computer science; Marketing; Psychology; Mathematics; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000441893,0.000106828,0.000187059,0.0001720695,0.00009819909,0.0001650832,0.0002317516,0.0000467313,0.0006081704],"category_scores_gemma":[0.0006046551,0.00009331761,0.0001199368,0.0003441325,0.00003462511,0.0007832043,0.0000869025,0.0002261623,0.0004486544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002811374,"about_ca_system_score_gemma":0.00004184218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001834066,"about_ca_topic_score_gemma":0.00000238091,"domain_scores_codex":[0.9991914,0.0000177029,0.0003531214,0.0001104747,0.0001704835,0.0001567967],"domain_scores_gemma":[0.9991564,0.00006153076,0.0004034329,0.00006888712,0.0002738746,0.00003587107],"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":[0.00008470413,0.0001327638,0.006165608,0.0003336434,0.00006643981,0.00003258653,0.0004374315,0.00001515166,0.001197335,0.02544507,0.9527251,0.01336419],"study_design_scores_gemma":[0.0006078664,0.00002448262,0.01032762,0.00008333426,0.0001088024,0.00000887267,0.0003283678,0.001533293,0.0001139878,0.0008521184,0.9858646,0.0001465957],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4759768,0.001368013,0.004049569,0.0437949,0.004509429,0.0003097059,0.000001338664,0.0001659822,0.4698243],"genre_scores_gemma":[0.9889797,0.00001310532,0.0001608626,0.002443622,0.007389693,0.000001576569,0.000005015261,0.00001773989,0.0009886683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.513003,"threshold_uncertainty_score":0.6659039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0310205536305586,"score_gpt":0.2572658696695734,"score_spread":0.2262453160390148,"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."}}