{"id":"W6887210977","doi":"10.15468/dl.tz5gwv","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Identification (biology); Data set","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":[0.001042652,0.00199636,0.001582392,0.005370665,0.0009800806,0.002655575,0.00286847,0.001913525,0.1652766],"category_scores_gemma":[0.006130205,0.0009215052,0.00120544,0.01027893,0.0004567624,0.00224462,0.002675973,0.001905191,0.2324122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156042,"about_ca_system_score_gemma":0.002343243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0211242,"about_ca_topic_score_gemma":0.03445684,"domain_scores_codex":[0.9988897,0.000151459,0.0001443744,0.0003772627,0.0002501823,0.0001870442],"domain_scores_gemma":[0.997489,0.0006582945,0.0002400618,0.0006965753,0.0006200455,0.0002961243],"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":[0.00003068993,0.00001046014,0.0003490987,0.0005553256,0.00001577489,0.00001439551,0.00002325228,0.0001106591,0.0001241018,0.0003970863,0.9969044,0.00146469],"study_design_scores_gemma":[0.00006443472,0.000007290629,0.001689555,0.000177377,0.00001394384,0.00003391335,0.00006046078,0.0001159979,0.0001878485,0.0007404084,0.9968927,0.00001603708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000039354,0.00002795533,0.00004286429,0.0000310168,0.00001057152,0.000005115417,0.9987904,0.0003900983,0.0006625811],"genre_scores_gemma":[0.0001488138,0.00003252942,0.0001714897,0.00004259805,0.000003142219,0.00003699949,0.9989808,0.0001518396,0.0004316918],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8347234,"threshold_uncertainty_score":0.5529053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437393559742932,"score_gpt":0.2320798631925623,"score_spread":0.217705927595133,"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."}}