{"id":"W6931209035","doi":"10.5281/zenodo.2433719","title":"Common attribute schema (CAS) for forest inventories across Canada","year":2011,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Radioactive contamination and transfer","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Schema (genetic algorithms); Boreal; Taiga; Ecosystem; Work (physics); Resource (disambiguation)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003750862,0.001212152,0.000754328,0.008385289,0.003159931,0.005872664,0.003505955,0.001040837,0.01508097],"category_scores_gemma":[0.008762038,0.001201402,0.001710472,0.02041158,0.001027168,0.003855506,0.001892736,0.002062574,0.00535208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02379189,"about_ca_system_score_gemma":0.05859884,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9417723,"about_ca_topic_score_gemma":0.9365777,"domain_scores_codex":[0.9971662,0.0001838628,0.0005692172,0.0004380795,0.001351944,0.0002906673],"domain_scores_gemma":[0.9889504,0.001333924,0.000640701,0.00183799,0.006635934,0.0006009467],"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":[0.0003096238,0.0001100957,0.02992405,0.001044024,0.0002887761,0.0004033081,0.001495991,0.0177074,0.003536522,0.1522807,0.5654266,0.2274729],"study_design_scores_gemma":[0.00003442317,0.00001125914,0.009655586,0.0002886828,0.00006476419,0.0002149338,0.0003954224,0.01074268,0.00233161,0.01249684,0.9636486,0.0001152875],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.009233825,0.001711844,0.2280148,0.001609402,0.0002641028,0.00116471,0.6842005,0.02242632,0.05137441],"genre_scores_gemma":[0.05655614,0.002258908,0.245729,0.0007879467,0.00005040433,0.001315204,0.6715168,0.003434893,0.01835065],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05822772,"threshold_uncertainty_score":0.172623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04672825067933976,"score_gpt":0.2403052013163532,"score_spread":0.1935769506370135,"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."}}