{"id":"W2810072327","doi":"10.1007/s13595-018-0743-5","title":"The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3): customization of the Archive Index Database for European Union countries","year":2018,"lang":"en","type":"article","venue":"Annals of Forest Science","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Joint Research Centre","keywords":"Metadata; Database; Context (archaeology); Transparency (behavior); European union; Index (typography); Computer science; Environmental resource management; World Wide Web; Business; Geography; Environmental science; International trade","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002796343,0.0006975782,0.0005674376,0.001578794,0.001368237,0.002853933,0.003144224,0.0007565125,0.009141527],"category_scores_gemma":[0.005938338,0.0004842519,0.001219787,0.00387656,0.0004828065,0.001624918,0.001465559,0.00141125,0.00230355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01158145,"about_ca_system_score_gemma":0.02031837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8605501,"about_ca_topic_score_gemma":0.8204464,"domain_scores_codex":[0.9987651,0.0001669483,0.00009117251,0.0001555359,0.0006538156,0.0001674993],"domain_scores_gemma":[0.9975352,0.0003193397,0.00008340331,0.0004937561,0.001375642,0.0001926992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000584483,0.0001534476,0.02314368,0.0004438777,0.0002140179,0.0002601065,0.0004007593,0.5420271,0.002016495,0.06491644,0.2906167,0.07522289],"study_design_scores_gemma":[0.0003344322,0.00004087812,0.01384985,0.0003466252,0.00009512573,0.00007835763,0.0003747237,0.4220907,0.005107179,0.01263572,0.5447588,0.0002877209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.09726308,0.001012953,0.09547249,0.002760247,0.0008010373,0.001292496,0.6055611,0.0163668,0.1794699],"genre_scores_gemma":[0.3918475,0.001534332,0.1798578,0.0006765326,0.00009731775,0.001385533,0.3989691,0.004888379,0.02074346],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8605501,"threshold_uncertainty_score":0.2805423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02637998589150399,"score_gpt":0.2602061889575669,"score_spread":0.2338262030660629,"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."}}