{"id":"W6984732552","doi":"","title":"Machine","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Process (computing); Work (physics); Set (abstract data type); Identification (biology); Troubleshooting","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":[0.0004779545,0.001791758,0.0008279793,0.001812178,0.0008484307,0.002652561,0.001926121,0.001341121,0.2425176],"category_scores_gemma":[0.002969201,0.0004319077,0.001032723,0.001811131,0.0003551707,0.002895823,0.00145682,0.001187325,0.2300398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007846208,"about_ca_system_score_gemma":0.001163425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008299373,"about_ca_topic_score_gemma":0.009525072,"domain_scores_codex":[0.9993564,0.00004985426,0.0000272618,0.0002966877,0.0001803015,0.00008953321],"domain_scores_gemma":[0.999284,0.0001273884,0.00002513463,0.0002813801,0.0002281819,0.00005403692],"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":[0.0001175107,0.00005876041,0.0003396886,0.0001133682,0.00001744601,0.00003824255,0.00002138347,0.001384425,0.001885321,0.00532357,0.5838327,0.4068677],"study_design_scores_gemma":[0.00007921582,0.00007704612,0.001083651,0.0001047391,0.00004531256,0.0002373407,0.00008469667,0.07020127,0.01486341,0.03125944,0.8819199,0.00004392062],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007579483,0.002191602,0.3315417,0.002450396,0.00277661,0.0006579717,0.0691749,0.2513805,0.3322468],"genre_scores_gemma":[0.08008306,0.001624873,0.2709247,0.002290396,0.0007912587,0.0008695922,0.1438402,0.01273936,0.4868365],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2425176,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001492640881456211,"score_gpt":0.1221327325497512,"score_spread":0.120640091668295,"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."}}