{"id":"W6926688373","doi":"10.25549/one-c4-4418","title":"Weathers photograph album 12, 1988-1992","year":2021,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"Microbial Metabolism and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Photography; Line drawings; Feature (linguistics); Subject (documents)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003878622,0.001757471,0.001108619,0.004043892,0.0006151622,0.002188452,0.001616069,0.0008367526,0.2062846],"category_scores_gemma":[0.003005194,0.0006566006,0.000529481,0.01062812,0.0002213368,0.001423387,0.001008566,0.001154667,0.2423284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001715542,"about_ca_system_score_gemma":0.002160251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1012698,"about_ca_topic_score_gemma":0.1960829,"domain_scores_codex":[0.9996352,0.00003006129,0.00003639107,0.0001143171,0.0001218543,0.00006215672],"domain_scores_gemma":[0.9987664,0.0002043745,0.0001488187,0.0001995763,0.0004786699,0.0002021612],"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":[0.00001169786,0.000002956966,0.0001346691,0.0001074335,0.000003100881,0.000004146707,0.000003830556,0.00004820228,0.0000160089,0.00009908206,0.9985985,0.0009704279],"study_design_scores_gemma":[0.00006945831,0.000003478576,0.002563525,0.0001052942,0.000008516677,0.00001027319,0.00003329586,0.0001388698,0.0000968376,0.0003213886,0.9966396,0.000009531959],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003634547,0.0000389155,0.000016554,0.00002483737,0.00001012348,0.000003195461,0.9982894,0.0001892179,0.001391319],"genre_scores_gemma":[0.0002065863,0.00007294825,0.0001054228,0.00001870813,0.000006829996,0.00002056288,0.9968945,0.0001041684,0.002570221],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2062846,"threshold_uncertainty_score":0.6900907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004203490170505467,"score_gpt":0.1592857496661664,"score_spread":0.155082259495661,"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."}}