{"id":"W6906010146","doi":"10.15468/dl.w8u7q8","title":"Occurrence Download","year":2023,"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); Real world data; 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":[0.001026736,0.002037977,0.001647997,0.004657223,0.001038752,0.002505672,0.002955708,0.00213447,0.1444508],"category_scores_gemma":[0.005984943,0.0009567518,0.001213387,0.009254458,0.0004689964,0.002265891,0.002561774,0.002129467,0.2012002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165187,"about_ca_system_score_gemma":0.002363201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02225309,"about_ca_topic_score_gemma":0.03583772,"domain_scores_codex":[0.999001,0.0001345667,0.0001317115,0.0003450239,0.0002224736,0.0001652899],"domain_scores_gemma":[0.9976191,0.0006960293,0.0002193821,0.0006258346,0.000569693,0.0002699679],"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":[0.00003146502,0.00001241095,0.0003956945,0.0005749454,0.00001616457,0.00001640599,0.0000269255,0.0001456223,0.0001447141,0.0003889218,0.9967535,0.001493157],"study_design_scores_gemma":[0.00007925754,0.000008495299,0.001885182,0.0001926009,0.00001519362,0.00003980108,0.00007807878,0.0001770362,0.0002155169,0.0007532148,0.9965367,0.00001890873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004307343,0.00002517267,0.00004878946,0.00003396086,0.00001194003,0.000005395922,0.9988549,0.0004123639,0.0005643941],"genre_scores_gemma":[0.0001542958,0.00002944663,0.0002121917,0.00003941642,0.000002954386,0.00004233494,0.999,0.0001477948,0.0003715556],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8555492,"threshold_uncertainty_score":0.483236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}