{"id":"W3173941778","doi":"10.5281/zenodo.3755958","title":"Science, Technical and Strategic benefits of Canadian partnership with Subaru","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of British Columbia; Queen's University; McMaster University; University of Waterloo","funders":"","keywords":"General partnership; Business; Political science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004570615,0.0007992442,0.000412746,0.001878417,0.009978189,0.005983111,0.001042526,0.002267253,0.02156477],"category_scores_gemma":[0.005982514,0.0003708867,0.0005231553,0.00263953,0.002083344,0.001864305,0.005812735,0.003078219,0.004964249],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0399826,"about_ca_system_score_gemma":0.1793386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.84825,"about_ca_topic_score_gemma":0.9340065,"domain_scores_codex":[0.9936885,0.0005081645,0.0001063643,0.0003796967,0.003592101,0.001725132],"domain_scores_gemma":[0.9871034,0.0004832968,0.0003962056,0.0003413835,0.005250286,0.0064254],"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":[0.0005982404,0.0001258258,0.008018629,0.0004194005,0.00007325912,0.001407532,0.002047093,0.001102794,0.005102032,0.1411734,0.6976197,0.1423121],"study_design_scores_gemma":[0.00002656029,0.00003836375,0.003341304,0.00007436618,0.00001165153,0.0003287272,0.0006475702,0.0002993961,0.000744256,0.003597595,0.9908568,0.00003343904],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02557093,0.02312329,0.006787906,0.4331692,0.007994425,0.00024374,0.005378665,0.001433779,0.4962981],"genre_scores_gemma":[0.354261,0.02378956,0.0371883,0.05550332,0.002140077,0.0001668123,0.005277006,0.0008939827,0.5207799],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9600174,"threshold_uncertainty_score":0.3052874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03482232226472658,"score_gpt":0.2362033591074351,"score_spread":0.2013810368427085,"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."}}