{"id":"W6894043512","doi":"10.5281/zenodo.6255770","title":"Sisyra nigra Retzius","year":2006,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dorsum; Ridge; Holarctic; Tapering; Perch","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":[0.00006618638,0.0004274599,0.0002391842,0.001334217,0.0008965839,0.0002706814,0.0002665312,0.0002295897,0.004256927],"category_scores_gemma":[0.0001500613,0.0001646363,0.0001811124,0.0004424101,0.0003885775,0.0003400699,0.0005871995,0.0002806385,0.002154175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002552584,"about_ca_system_score_gemma":0.0001405677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004336994,"about_ca_topic_score_gemma":0.01295969,"domain_scores_codex":[0.9999255,0.000005433045,0.000007895119,0.00003110887,0.00002171621,0.000008354183],"domain_scores_gemma":[0.9999269,0.000008461115,0.00003199062,0.000009408122,0.00001376682,0.0000094942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0010318,0.0002492752,0.1079751,0.001177057,0.0002036114,0.009617368,0.005068311,0.001412386,0.4818932,0.003462753,0.005339936,0.3825693],"study_design_scores_gemma":[0.00008503996,0.0007789396,0.8140017,0.0002617989,0.0002234016,0.02052827,0.002466955,0.001583824,0.0201862,0.001016487,0.1387951,0.00007227973],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8934793,0.001921376,0.001111081,0.0001219934,0.00008458944,0.00009481711,0.0007206598,0.0004334696,0.1020326],"genre_scores_gemma":[0.9844412,0.0005200312,0.001392263,0.00007993036,0.00002289779,0.00002249602,0.0005801478,0.00002075959,0.01292034],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.004336994,"threshold_uncertainty_score":0.01424086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440188765265937,"score_gpt":0.181606101447574,"score_spread":0.1672042137949146,"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."}}