{"id":"W6891607532","doi":"10.4224/40003404","title":"La recherche, accélérateur de l’innovation pour le Canada : plan stratégique du CNRC pour 2024-2029","year":2024,"lang":"fr","type":"report","venue":"NRC Digital Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Plan (archaeology); Government (linguistics); Context (archaeology); Work (physics)","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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.005872627,0.002169311,0.001737448,0.001053927,0.0004223677,0.003946543,0.001505782,0.00414498,0.0001189116],"category_scores_gemma":[0.01006296,0.002513434,0.0006791409,0.003080163,0.000448401,0.001716593,0.000694732,0.007560088,0.001428598],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.03860106,"about_ca_system_score_gemma":0.256375,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5288546,"about_ca_topic_score_gemma":0.3254022,"domain_scores_codex":[0.9859828,0.00181059,0.003311059,0.002688828,0.00409528,0.002111495],"domain_scores_gemma":[0.9884636,0.002722683,0.001969353,0.001792044,0.004139082,0.0009132398],"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":[0.000198244,0.0008324566,0.007566311,0.002426112,0.001878841,0.03565868,0.0003130012,0.0003934436,0.04572551,0.006919052,0.8628514,0.03523691],"study_design_scores_gemma":[0.0007739692,0.0001930343,0.004412895,0.003442672,0.0006658621,0.02465313,0.002202904,0.0004472395,0.02090206,0.005307989,0.93406,0.002938235],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1077239,0.005217285,0.000274727,0.0009599738,0.008929186,0.001041208,0.003108799,0.0007095145,0.8720354],"genre_scores_gemma":[0.4076075,0.000209872,0.0006939311,0.0001360131,0.003464921,0.0001901475,0.001019861,0.001009251,0.5856686],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2998836,"threshold_uncertainty_score":0.9993489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1485402254711876,"score_gpt":0.302919042128947,"score_spread":0.1543788166577593,"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."}}