{"id":"W4255493613","doi":"10.31399/asm.tb.hss.t52790229","title":"Canada Restores a Fleet of Stainless Steel Railcars","year":2010,"lang":"en","type":"book-chapter","venue":"ASM International eBooks","topic":"Metallurgy and Cultural Artifacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automotive engineering; Aeronautics; Environmental science; Engineering","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":[0.0004648385,0.0006533748,0.0003629226,0.00185355,0.006775509,0.002819676,0.001144298,0.0009138706,0.01595495],"category_scores_gemma":[0.0007956818,0.0002058935,0.000348746,0.002606043,0.001768639,0.0007601673,0.001140961,0.001119762,0.00176772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02522307,"about_ca_system_score_gemma":0.05066425,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9640941,"about_ca_topic_score_gemma":0.9918001,"domain_scores_codex":[0.9991754,0.00002754052,0.00001159359,0.000060078,0.0005342268,0.0001911638],"domain_scores_gemma":[0.9996057,0.00001539118,0.00001494021,0.00001459321,0.0003021228,0.00004737146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001358614,0.00007859262,0.005484293,0.001356613,0.00005138691,0.002633137,0.01023707,0.003694798,0.008160907,0.04714091,0.233775,0.6872514],"study_design_scores_gemma":[0.000002459161,0.00003295195,0.0057061,0.0003181681,0.0000133124,0.0003351238,0.003415996,0.0001897251,0.001152332,0.0005585818,0.9882586,0.00001666115],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1680375,0.0851246,0.01160257,0.01503444,0.003541165,0.0003174886,0.002291401,0.00114108,0.7129099],"genre_scores_gemma":[0.2953414,0.04186897,0.01198001,0.001527867,0.0001460327,0.00004159524,0.00115231,0.0003645217,0.6475772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0359059,"threshold_uncertainty_score":0.183007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587652582000531,"score_gpt":0.2675280669400577,"score_spread":0.2416515411200524,"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."}}