{"id":"W6928796025","doi":"10.4224/40000408","title":"100 years of innovation for Canada","year":2017,"lang":"en","type":"report","venue":"NRC Digital Repository","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Agency (philosophy); Field (mathematics)","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":[0.005122623,0.001233506,0.0009606915,0.004180779,0.005035705,0.01128462,0.001805447,0.005805864,0.1387766],"category_scores_gemma":[0.01136625,0.0005054826,0.00121832,0.004497314,0.002392601,0.002905822,0.005901805,0.004179984,0.0556432],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03000011,"about_ca_system_score_gemma":0.1851948,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7753689,"about_ca_topic_score_gemma":0.8293631,"domain_scores_codex":[0.9863418,0.0003594886,0.0002228992,0.0005068028,0.01015534,0.002413663],"domain_scores_gemma":[0.9799952,0.0006566102,0.000246786,0.0008376712,0.009458435,0.00880529],"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":[0.00003877551,0.00002907827,0.0003864619,0.00006023082,0.000007956382,0.0001006564,0.00006531813,0.0001032058,0.000165352,0.006397778,0.9730954,0.01954974],"study_design_scores_gemma":[0.000008748987,0.000007784041,0.0009156002,0.00005179751,0.000003346039,0.00002883516,0.00009736573,0.00005505283,0.00007308871,0.000451515,0.9982997,0.00000723472],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.009138243,0.02785745,0.002587423,0.1699894,0.06574482,0.0006930293,0.05198712,0.002751022,0.6692514],"genre_scores_gemma":[0.01149292,0.006765209,0.001424716,0.006049276,0.001212843,0.00009810739,0.008424081,0.0003347444,0.9641982],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9699999,"threshold_uncertainty_score":0.464254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376838702614191,"score_gpt":0.2575683101334492,"score_spread":0.2437999231073072,"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."}}