{"id":"W7033851758","doi":"","title":"St-Lawrence Routing Ice Management Support Model Project–NRC Input, Year 2","year":2003,"lang":"en","type":"report","venue":"NPARC","topic":"Entomological Studies and Ecology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Routing (electronic design automation); Work (physics); Sea ice; Automation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001645982,0.001346889,0.001048359,0.001731573,0.0007892332,0.001506562,0.003062989,0.0007897026,0.05827127],"category_scores_gemma":[0.006132079,0.001219786,0.0006634014,0.004534149,0.000244782,0.001677727,0.0006348892,0.00111359,0.02280174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008295038,"about_ca_system_score_gemma":0.01584576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5536094,"about_ca_topic_score_gemma":0.614211,"domain_scores_codex":[0.9987034,0.0001790311,0.0000566257,0.0001249338,0.0007301747,0.0002057719],"domain_scores_gemma":[0.995031,0.0003473441,0.0002528842,0.0003157184,0.003829323,0.0002236694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003459194,0.0001155782,0.005817239,0.0002073823,0.00004196118,0.00005648303,0.00002776312,0.01574762,0.0001690989,0.001161036,0.9580951,0.01821481],"study_design_scores_gemma":[0.001105704,0.0001870707,0.0549719,0.000367801,0.0001870836,0.0001184135,0.0003729804,0.05005413,0.0043489,0.002496339,0.885676,0.0001135241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01050116,0.0001871083,0.001844496,0.001088065,0.0005812844,0.0005101134,0.9064723,0.001400549,0.07741491],"genre_scores_gemma":[0.06974796,0.0007587824,0.009348742,0.000486117,0.0001205018,0.0009365661,0.7450966,0.001884366,0.1716203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5536094,"threshold_uncertainty_score":0.8980389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.072653674780532,"score_gpt":0.2822488183078786,"score_spread":0.2095951435273466,"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."}}