{"id":"W6962438507","doi":"10.15468/dl.ygye66","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Range (aeronautics); State (computer science); 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":[0.000946589,0.001924689,0.001459488,0.004591298,0.000935811,0.002299156,0.002662546,0.001849361,0.1422908],"category_scores_gemma":[0.005650652,0.0008897603,0.001117031,0.00870572,0.0004387991,0.002010249,0.002247961,0.0019648,0.1907974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001487468,"about_ca_system_score_gemma":0.002263824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01899221,"about_ca_topic_score_gemma":0.03198154,"domain_scores_codex":[0.9990075,0.0001384083,0.0001300399,0.0003592636,0.0002079298,0.0001568916],"domain_scores_gemma":[0.9977737,0.00064769,0.0002185882,0.0005515578,0.0005456214,0.000262781],"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":[0.00003323122,0.00001272014,0.0003868489,0.0004882185,0.0000142424,0.00001416798,0.00002048423,0.0001344133,0.0001157232,0.0003885393,0.9970645,0.001326878],"study_design_scores_gemma":[0.00009434754,0.000009320439,0.00186708,0.0001603796,0.0000153123,0.00003672438,0.00006477408,0.0001941638,0.0002101831,0.000917265,0.9964119,0.00001854952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004892259,0.0000223827,0.00004860366,0.00003299457,0.00001138706,0.000005822866,0.9988322,0.0003765369,0.0006212331],"genre_scores_gemma":[0.0001757006,0.00002987214,0.0002291267,0.0000460032,0.000003523269,0.00004941847,0.9988455,0.0001608336,0.0004601053],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8577092,"threshold_uncertainty_score":0.4760101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06850837321744672,"score_gpt":0.304165618038287,"score_spread":0.2356572448208403,"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."}}