{"id":"W4404836992","doi":"10.15353/whr.v10.6144","title":"Contents","year":2024,"lang":"en","type":"paratext","venue":"Waterloo Historical Review","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004660848,0.0007664958,0.0007869127,0.004178286,0.00118833,0.004533804,0.0009991546,0.0006981974,0.6849438],"category_scores_gemma":[0.003158534,0.0002763984,0.0003817425,0.0048769,0.0005539696,0.002285668,0.001380004,0.001360902,0.5467239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003098039,"about_ca_system_score_gemma":0.00282357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01276609,"about_ca_topic_score_gemma":0.01783688,"domain_scores_codex":[0.9995193,0.00005262838,0.00002287729,0.00006245401,0.0002962593,0.00004644686],"domain_scores_gemma":[0.9982646,0.0002532907,0.00009778953,0.000161119,0.0009281897,0.0002950112],"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":[0.000005298508,0.000007144256,0.0000318856,0.000074066,7.862756e-7,0.000002957282,0.000007576636,0.00001663534,0.00005323907,0.0009964688,0.9816158,0.01718818],"study_design_scores_gemma":[0.000001472016,0.000002774293,0.0002281342,0.0001042494,0.00000144269,0.00001038613,0.00001468471,0.00001965754,0.00003763736,0.0005483157,0.9990298,0.000001449182],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003243638,0.01409334,0.001012564,0.006807503,0.02327685,0.0001728377,0.009919685,0.0007820587,0.9436107],"genre_scores_gemma":[0.001397639,0.007954616,0.0004047803,0.001676353,0.008739016,0.0000642605,0.006127048,0.0003351998,0.9733011],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3150562,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08752622061654551,"score_gpt":0.2462094352492237,"score_spread":0.1586832146326782,"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."}}