{"id":"W6911214226","doi":"10.5281/zenodo.10167366","title":"Parocyusa fuliginosa","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Coleoptera Taxonomy and Distribution","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Agriculture and Agri-Food Canada; Canadian Forest Service","funders":"","keywords":"Floodplain; Plant litter; Table (database); Swamp; STREAMS; Karst","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001154471,0.0006088144,0.0002238016,0.001000429,0.001150544,0.0003924782,0.0004705519,0.0004652588,0.006366058],"category_scores_gemma":[0.0004103739,0.0001936994,0.0002344671,0.0005682327,0.0005582969,0.0006865734,0.0008530978,0.0004910605,0.002543456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009971168,"about_ca_system_score_gemma":0.000356399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02843217,"about_ca_topic_score_gemma":0.04174651,"domain_scores_codex":[0.9998635,0.00001118839,0.00001074623,0.00004499183,0.00003327779,0.00003632409],"domain_scores_gemma":[0.9998831,0.00001679343,0.00004244188,0.00001640084,0.00002458079,0.00001674285],"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":[0.0009929225,0.0002727644,0.08131392,0.00127214,0.00006953889,0.02206325,0.00418516,0.001762668,0.1416699,0.004968977,0.03249678,0.708932],"study_design_scores_gemma":[0.0002194778,0.001059904,0.5768886,0.0008901093,0.0001291688,0.02475829,0.00405688,0.002113113,0.01118524,0.002278698,0.3763468,0.00007368396],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.881426,0.006683056,0.001846093,0.0006635745,0.000242795,0.0002195352,0.002069575,0.0003019327,0.1065474],"genre_scores_gemma":[0.9802869,0.001453354,0.001867338,0.0005251524,0.00006379589,0.0001081806,0.001751678,0.00001564473,0.013928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02843217,"threshold_uncertainty_score":0.05653334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04725378221668926,"score_gpt":0.225545288194586,"score_spread":0.1782915059778967,"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."}}