{"id":"W6924833401","doi":"10.15468/dl.x4oakx","title":"Occurrence Download","year":2016,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Libraries and Information Services","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); Download; Identification (biology)","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":[0.0009336674,0.002169899,0.001560444,0.00533285,0.0009204065,0.002724966,0.002961772,0.001805362,0.1399703],"category_scores_gemma":[0.005629318,0.0008818679,0.001161825,0.01115542,0.0004343917,0.00235022,0.002691662,0.001973365,0.2217002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001682974,"about_ca_system_score_gemma":0.002682632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02532204,"about_ca_topic_score_gemma":0.0458295,"domain_scores_codex":[0.9988754,0.0001480522,0.0001474371,0.0003780536,0.0002671085,0.0001839802],"domain_scores_gemma":[0.9977269,0.0005575842,0.0002477923,0.0005857677,0.0005915714,0.0002905058],"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":[0.00002548764,0.000009611254,0.0003733171,0.0003937834,0.00001242421,0.0000128216,0.00001964507,0.00009985839,0.0000803256,0.0003902687,0.9972994,0.001283028],"study_design_scores_gemma":[0.00005371014,0.000006204352,0.001565603,0.00014798,0.00001149164,0.00003336902,0.00005358163,0.0001197112,0.000159079,0.0007249494,0.9971095,0.00001483952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004073276,0.00002888479,0.00004116569,0.00003312639,0.00001119361,0.000004380859,0.998736,0.0003578087,0.0007467545],"genre_scores_gemma":[0.0001295871,0.00003474325,0.000153971,0.00003682712,0.000003141808,0.0000309791,0.9989177,0.0001306478,0.0005624157],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8600297,"threshold_uncertainty_score":0.4682473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02271281429207935,"score_gpt":0.1966796248036959,"score_spread":0.1739668105116165,"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."}}