{"id":"W6966873169","doi":"10.4224/40003418","title":"2023–2024 annual report: driving research and innovation for Canada's future","year":2024,"lang":"en","type":"report","venue":"NRC Digital Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Production (economics); Quality (philosophy)","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":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003469656,0.0007907662,0.0009015138,0.002081033,0.0004573481,0.002119614,0.0006780782,0.0009699233,0.00001089595],"category_scores_gemma":[0.01031813,0.0007915929,0.0001945341,0.003171119,0.0003439143,0.0008851765,0.001082178,0.002241014,0.00006354925],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.007821904,"about_ca_system_score_gemma":0.03478757,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09702846,"about_ca_topic_score_gemma":0.2014361,"domain_scores_codex":[0.9876153,0.00006728102,0.001902246,0.002098791,0.007151633,0.001164739],"domain_scores_gemma":[0.9834206,0.0005455058,0.0008714786,0.00180362,0.01302179,0.0003370518],"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":[0.0000461176,0.00006133525,0.001623538,0.001395394,0.000398852,0.007841568,0.00006751854,0.000001063326,0.0005987622,0.0004432279,0.9736251,0.01389755],"study_design_scores_gemma":[0.0001474067,0.0001739764,0.001301017,0.001106559,0.0001095839,0.007546145,0.0005835054,0.000007082281,0.0004194774,0.001389202,0.9864527,0.0007633376],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03964214,0.009632336,0.000009135322,0.0005915118,0.03246716,0.002361126,0.006514907,0.000502924,0.9082788],"genre_scores_gemma":[0.1103394,0.00005710064,0.0001057148,0.00001815742,0.0120907,0.000513598,0.002226985,0.0007175545,0.8739308],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1044077,"threshold_uncertainty_score":0.9994535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03830026330103261,"score_gpt":0.3460421449565693,"score_spread":0.3077418816555367,"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."}}