{"id":"W4394528686","doi":"10.6084/m9.figshare.22581703","title":"Urban rail stocks 1978-2020","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"transportation and logistics systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency","funders":"","keywords":"Transport engineering; Business; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004311631,0.00154242,0.0009456735,0.006896251,0.0004587898,0.001501813,0.00133248,0.001066074,0.02972087],"category_scores_gemma":[0.003578211,0.0007295916,0.001146643,0.01627933,0.0002798324,0.0007597198,0.001043623,0.000993019,0.03033463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001305007,"about_ca_system_score_gemma":0.002711637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1665678,"about_ca_topic_score_gemma":0.1722976,"domain_scores_codex":[0.9993539,0.00004436005,0.00009207935,0.0001826072,0.0001759959,0.000151071],"domain_scores_gemma":[0.9984702,0.0002402388,0.0004036506,0.0002010735,0.0005319922,0.000152723],"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":[0.0001667249,0.00004013326,0.01864113,0.0008352362,0.0001770984,0.00006098112,0.00005490209,0.001576682,0.0001633526,0.0006003289,0.9705526,0.007130762],"study_design_scores_gemma":[0.0005066257,0.0000533319,0.1561509,0.0007436043,0.0002065189,0.0001494511,0.0004060416,0.001523797,0.0006113422,0.0006554748,0.8389247,0.00006816877],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008653409,0.00005782368,0.00001571952,0.00002496882,0.000009940563,0.000002973255,0.998715,0.00004444637,0.0002637604],"genre_scores_gemma":[0.001693382,0.00008655856,0.00005351303,0.00001533406,0.000006068631,0.00002273887,0.9973231,0.00001190433,0.0007874545],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1665678,"threshold_uncertainty_score":0.3311965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08079285316680251,"score_gpt":0.3385130131838993,"score_spread":0.2577201600170968,"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."}}