{"id":"W6968795029","doi":"10.5281/zenodo.4511467","title":"Gimnomera","year":2020,"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":"Canadian Food Inspection Agency; McGill University","funders":"","keywords":"Nearctic ecozone; Biodiversity; Watt; Context (archaeology)","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":[0.000135719,0.0009751372,0.0003012125,0.001235663,0.002043688,0.0004740949,0.0006659987,0.0005992202,0.03075481],"category_scores_gemma":[0.0003016473,0.0003437148,0.0004178731,0.0008580454,0.0008601804,0.0007823649,0.00134507,0.000908269,0.00834271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001015252,"about_ca_system_score_gemma":0.0005799389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02345541,"about_ca_topic_score_gemma":0.05419813,"domain_scores_codex":[0.9998451,0.00001396027,0.000007724579,0.00006494981,0.00003658838,0.00003152035],"domain_scores_gemma":[0.9999267,0.00000843221,0.00002392662,0.00001384851,0.00001571794,0.00001133458],"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":[0.001038029,0.0002512658,0.05198821,0.002163572,0.0001963505,0.00459804,0.006337878,0.00142487,0.07832175,0.03619959,0.09006947,0.727411],"study_design_scores_gemma":[0.00007452365,0.0001962134,0.290474,0.0007394606,0.0001467917,0.004463067,0.001433988,0.0005504793,0.002409033,0.00271593,0.6967574,0.00003910039],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.277759,0.008590212,0.006416504,0.001765609,0.0005726505,0.0007539124,0.01088085,0.001843457,0.6914178],"genre_scores_gemma":[0.8403162,0.003564322,0.01581505,0.002638947,0.0002270215,0.0004965116,0.008186354,0.0002457405,0.1285098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03075481,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03307683223513735,"score_gpt":0.1934930959279414,"score_spread":0.160416263692804,"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."}}