{"id":"W6947749497","doi":"10.4224/40002751","title":"Responding to Canada's needs: from COVID-19 to climate change: annual report 2019-2020","year":2020,"lang":"en","type":"report","venue":"NRC Digital Repository","topic":"Subterranean biodiversity and taxonomy","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Annual report; Climate change; Annual cycle; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003909474,0.0005621939,0.0007455658,0.000533077,0.0004501037,0.0006050325,0.0008280511,0.000351155,0.000400839],"category_scores_gemma":[0.001568288,0.0005777659,0.000231164,0.000975219,0.00006702401,0.0004932846,0.0002626381,0.0004819825,0.0005486726],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006151777,"about_ca_system_score_gemma":0.006287563,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7948559,"about_ca_topic_score_gemma":0.5449252,"domain_scores_codex":[0.9948491,0.00007141276,0.0007702486,0.00116358,0.002373029,0.0007726473],"domain_scores_gemma":[0.9959447,0.0002487596,0.0004612539,0.0006980436,0.0003287035,0.002318489],"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":[0.0004172032,0.00001542816,0.4021926,0.0001297072,0.0001277953,0.01656475,0.0009275279,0.00006723272,0.000003250745,6.42531e-7,0.5569995,0.02255433],"study_design_scores_gemma":[0.0001342796,0.0001725397,0.06551469,0.0001549967,0.00006655478,0.0006556901,0.0009017776,0.000005542603,0.0000168953,0.00000414721,0.9316817,0.0006911801],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06766897,0.001731787,0.00004492995,0.004137379,0.01631584,0.001943592,0.04479843,0.00046867,0.8628904],"genre_scores_gemma":[0.9349126,0.0001484906,0.0002693071,0.009495975,0.008100099,0.00002590638,0.007701036,0.00005467316,0.03929186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8672436,"threshold_uncertainty_score":0.9996674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0508570424174691,"score_gpt":0.2371016538324266,"score_spread":0.1862446114149575,"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."}}