{"id":"W6961208166","doi":"10.14288/1.0225563","title":"Canadian Pacific Steamships agent's stubs","year":2016,"lang":"en","type":"article","venue":"Open Collections","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ticket; Government (linguistics); Asia pacific; Pacific Area; Indian ocean","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009286271,0.00007415525,0.00006782104,0.00003140774,0.001110765,0.0002721587,0.0002386986,0.00006625411,0.0008361312],"category_scores_gemma":[0.00003222428,0.00005627031,0.00003722961,0.0001270726,0.00002472646,0.000003372207,0.00009738253,0.00002574093,0.00006107621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003087487,"about_ca_system_score_gemma":0.0002380483,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06089813,"about_ca_topic_score_gemma":0.1376406,"domain_scores_codex":[0.999435,0.00003133377,0.00007541195,0.0002083453,0.00005114206,0.000198735],"domain_scores_gemma":[0.9995661,0.00000738376,0.00002171573,0.0001881718,0.00004853764,0.0001680701],"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":[0.00001752102,0.00002463751,0.00133155,0.000001133047,0.00003661038,0.000003279065,0.00001670292,0.000002246669,0.01305318,0.00004468991,0.9841852,0.001283227],"study_design_scores_gemma":[0.0003641882,0.000118953,0.0007485699,0.000009818886,0.000007409211,0.00001433706,0.0003081499,0.000001487433,0.003544574,0.0001407453,0.9946147,0.0001270842],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02997994,0.00007320406,0.0003863748,0.001431525,0.0003971147,0.0003103228,0.0003739118,0.00001269421,0.9670349],"genre_scores_gemma":[0.5020542,0.0001139625,0.0001388456,0.0001305054,0.0000682289,0.00001310098,0.00001981963,0.000005084862,0.4974563],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4720742,"threshold_uncertainty_score":0.9453554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812480319107566,"score_gpt":0.22663030963629,"score_spread":0.2085055064452143,"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."}}