{"id":"W6966885102","doi":"10.4224/23001608","title":"Canadian Science and Engineering Hall of Fame: finding aid","year":2017,"lang":"en","type":"article","venue":"NPARC","topic":"Diverse Education and Engineering Focus","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Field (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003950598,0.00002741767,0.00003941173,0.00008968317,0.0005227476,0.0001208399,0.0002340235,0.00001930305,0.0001170871],"category_scores_gemma":[0.0006907869,0.00003047884,0.000006976673,0.00007135781,0.0002068362,0.0001924608,0.00002119485,0.00003422869,0.000008094822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001123406,"about_ca_system_score_gemma":0.0004636152,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08468379,"about_ca_topic_score_gemma":0.02904536,"domain_scores_codex":[0.9995704,0.00000263445,0.00003680871,0.00006919207,0.0001538956,0.0001670604],"domain_scores_gemma":[0.9996201,0.00001218426,0.00001995464,0.000110549,0.00005759853,0.000179647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000182964,0.00001907013,0.03897388,0.00004092748,0.0000137107,0.000007644172,0.03867379,0.0001309177,0.03407291,0.8411078,0.005666523,0.04129102],"study_design_scores_gemma":[0.0004282768,0.00002959245,0.2590527,0.0001369012,0.00001672383,0.000002251784,0.007027261,0.002992435,0.004237391,0.002507721,0.7230804,0.0004883503],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6410461,0.0000111841,0.0000192444,0.002515157,0.0006963164,0.00004297314,0.000002308142,0.00001823109,0.3556485],"genre_scores_gemma":[0.998107,0.00001249538,0.0009359946,0.00001592021,0.00004973635,0.000001069991,8.191743e-8,0.000002150723,0.0008755608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8386,"threshold_uncertainty_score":0.988672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316793622098066,"score_gpt":0.2795023625605412,"score_spread":0.2563344263395605,"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."}}