{"id":"W6931342983","doi":"10.5281/zenodo.7888712","title":"Rosa arvensis Huds.","year":2014,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"","keywords":"Identification (biology); Selection (genetic algorithm); Taxonomy (biology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002205418,0.0007767311,0.0006090074,0.001060903,0.0006785063,0.0005738176,0.0006080542,0.000292235,0.01539492],"category_scores_gemma":[0.0001419699,0.0002090634,0.0003626618,0.0008987679,0.0001692798,0.0004258381,0.0004444587,0.0009428351,0.01431824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006419228,"about_ca_system_score_gemma":0.0002286091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01116967,"about_ca_topic_score_gemma":0.02011527,"domain_scores_codex":[0.9998393,0.00001240724,0.000008896837,0.00008602613,0.00003712868,0.00001607231],"domain_scores_gemma":[0.9998988,0.00001178259,0.00002132861,0.00001555923,0.00002737922,0.00002505616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000724128,0.0004948443,0.01082026,0.000837722,0.0002728275,0.002201237,0.0007673961,0.000757474,0.4309726,0.01263896,0.08606577,0.4534467],"study_design_scores_gemma":[0.0001335757,0.0002583369,0.09588899,0.0001101208,0.0001355015,0.001207973,0.0004543433,0.0002682697,0.0113983,0.002007396,0.8880934,0.0000436518],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4100722,0.04503618,0.01658624,0.003881105,0.002515189,0.0007587798,0.05518312,0.007800025,0.4581673],"genre_scores_gemma":[0.6077793,0.009764226,0.01234542,0.00206549,0.0002487634,0.0004336954,0.06639849,0.0007976537,0.3001671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01539492,"threshold_uncertainty_score":0.05150115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09246006177006104,"score_gpt":0.2043986455524213,"score_spread":0.1119385837823603,"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."}}