{"id":"W6892647035","doi":"10.5281/zenodo.11050152","title":"Linked collectors and determiners for: Royal Ontario Museum - Entomology (ROME).","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Entomology; Biodiversity; Citizen science; Natural history; Attribution; Natural (archaeology)","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":[0.001314812,0.001951779,0.001647128,0.005272803,0.001345332,0.002877925,0.002676902,0.001431696,0.1368987],"category_scores_gemma":[0.006807999,0.001161244,0.000774593,0.009740721,0.000591442,0.001741265,0.002433124,0.002161865,0.1803271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003600421,"about_ca_system_score_gemma":0.005559423,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1188527,"about_ca_topic_score_gemma":0.2558829,"domain_scores_codex":[0.9984984,0.0001201869,0.0001473983,0.0004728078,0.0005154307,0.0002457556],"domain_scores_gemma":[0.9956203,0.0006580538,0.0004709085,0.001166121,0.001620713,0.0004638346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001288202,0.000003945777,0.0004579291,0.0002282955,0.0000076178,0.0000065012,0.0000174363,0.00007210177,0.0000635476,0.0003009853,0.9972665,0.001562151],"study_design_scores_gemma":[0.00003387226,0.00000235119,0.002347531,0.000159893,0.000007410609,0.00001287581,0.00004544764,0.00007076195,0.0001463423,0.0004444774,0.9967147,0.00001442251],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003283045,0.00002037432,0.00005281451,0.00001797618,0.00001365676,0.000006241076,0.9987048,0.0001703011,0.0009809954],"genre_scores_gemma":[0.0001910759,0.00003126516,0.0003056668,0.00001850888,0.000004301611,0.00005534823,0.9976897,0.0001523945,0.001551782],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8811473,"threshold_uncertainty_score":0.4579717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02210916351811096,"score_gpt":0.2270765849256366,"score_spread":0.2049674214075257,"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."}}