{"id":"W6961863031","doi":"10.15468/dl.u38udu","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Alien; Range (aeronautics); 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":[0.0009200489,0.002020682,0.001548948,0.005055598,0.0009682711,0.002536285,0.002578924,0.001913246,0.1720003],"category_scores_gemma":[0.006290191,0.0008912278,0.001186778,0.01002716,0.0004332445,0.002175641,0.002533579,0.001779263,0.2260061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001471214,"about_ca_system_score_gemma":0.002236763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02065181,"about_ca_topic_score_gemma":0.03244846,"domain_scores_codex":[0.9989801,0.0001375093,0.000128615,0.0003670088,0.0002150785,0.0001716732],"domain_scores_gemma":[0.9975045,0.0007363048,0.0002437977,0.0006329238,0.0006094014,0.0002730172],"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":[0.00003224633,0.00001066741,0.0004036213,0.0005722709,0.00001455278,0.0000151941,0.00002304664,0.0001341574,0.0001215091,0.0003708297,0.9967585,0.001543406],"study_design_scores_gemma":[0.00007169749,0.000009751671,0.0018095,0.0001935821,0.00001483943,0.00003565955,0.00006722162,0.0001505739,0.0001829174,0.0007957762,0.9966504,0.00001805126],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004292757,0.00002673475,0.00004098752,0.0000339958,0.00001198584,0.000004982215,0.9988274,0.0003833068,0.0006277422],"genre_scores_gemma":[0.000168599,0.00003639071,0.0002029196,0.00004847735,0.000003827995,0.00004388385,0.9988201,0.000166853,0.0005089181],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8279997,"threshold_uncertainty_score":0.5753984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}