{"id":"W6906327512","doi":"10.15468/gdvlxf","title":"URM - Herbário Pe. Camille Torrand","year":2015,"lang":"pt","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Herbarium; Flora (microbiology); Lichen; State (computer science)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00035896,0.0005972881,0.000522966,0.001054329,0.001507951,0.0009112696,0.0006814302,0.0007970333,0.09380013],"category_scores_gemma":[0.0008715637,0.0001853639,0.0001701748,0.0005275973,0.0003572134,0.0006764079,0.001655681,0.001496583,0.02902047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067276,"about_ca_system_score_gemma":0.0008691102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009806343,"about_ca_topic_score_gemma":0.03214903,"domain_scores_codex":[0.9996184,0.00004153071,0.000007251527,0.00008914187,0.000203019,0.00004051963],"domain_scores_gemma":[0.9996761,0.00004143456,0.00003545881,0.00002277014,0.00008639956,0.0001377804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003896522,0.0001415395,0.002903634,0.001062776,0.0000179145,0.002732108,0.0009638294,0.0001648874,0.02324296,0.008098625,0.4680243,0.4922579],"study_design_scores_gemma":[0.000005497831,0.00004540667,0.004673723,0.0001067012,0.000002288243,0.000710059,0.0001107664,0.0000315649,0.0008102338,0.0002143216,0.9932847,0.00000483448],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.03543009,0.1533253,0.001719608,0.0196974,0.01040198,0.0003307732,0.002293885,0.0009197653,0.7758812],"genre_scores_gemma":[0.08756074,0.02860679,0.002721675,0.003370043,0.001990829,0.00007826077,0.001102346,0.0002006945,0.8743687],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.9061999,"threshold_uncertainty_score":0.3137927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0976240185197474,"score_gpt":0.3616152562114465,"score_spread":0.2639912376916991,"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."}}