{"id":"W6945591616","doi":"10.25549/examiner-c44-27145","title":"City Council, 1951","year":2021,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"George (robot); Ransom; Post office; Work (physics); Quarter (Canadian coin)","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":[0.0004877692,0.001994647,0.001129795,0.003378055,0.001000063,0.003769489,0.001636164,0.001186018,0.1396139],"category_scores_gemma":[0.003572483,0.0008325053,0.0007874423,0.009940542,0.0003477351,0.001919842,0.001519152,0.001850505,0.2586488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002140948,"about_ca_system_score_gemma":0.00248198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1237055,"about_ca_topic_score_gemma":0.2646441,"domain_scores_codex":[0.9993564,0.00006803043,0.00006093854,0.0001893199,0.0001825645,0.0001426543],"domain_scores_gemma":[0.9986678,0.0001517165,0.0001061971,0.0002575189,0.0006687199,0.0001480542],"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":[0.00001253336,0.000003256131,0.0002152266,0.00009068703,0.000003145308,0.00000460296,0.000008727257,0.00003699872,0.0000121213,0.0001709802,0.9983028,0.001138794],"study_design_scores_gemma":[0.00003869963,0.000003747165,0.002154328,0.0001570257,0.000005336304,0.00001650007,0.00008268929,0.00007896411,0.00006136683,0.0003389541,0.9970526,0.000009784182],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005809802,0.00007202165,0.00002464527,0.00004753577,0.00003389807,0.00000320558,0.997652,0.0001866869,0.001921898],"genre_scores_gemma":[0.0002426076,0.00007513756,0.0001140391,0.00002960844,0.000007201276,0.00001602877,0.9969084,0.00008496681,0.002522086],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1396139,"threshold_uncertainty_score":0.4670551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01659185696209643,"score_gpt":0.162374131080311,"score_spread":0.1457822741182146,"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."}}