{"id":"W6962007110","doi":"10.15468/dl.ks9fnk","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); Range (aeronautics); Download; Identification (biology); Set (abstract data type)","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":[0.0009580668,0.001974639,0.001478082,0.004591198,0.0008734463,0.00243969,0.002686493,0.001830796,0.1519659],"category_scores_gemma":[0.00580989,0.0008896904,0.001087002,0.008692862,0.0004297221,0.002045522,0.002286923,0.001933629,0.2049991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001491659,"about_ca_system_score_gemma":0.002286557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01780391,"about_ca_topic_score_gemma":0.03150643,"domain_scores_codex":[0.9990116,0.0001419616,0.0001274773,0.0003552703,0.0002100211,0.0001536245],"domain_scores_gemma":[0.9977136,0.0006748224,0.0002226833,0.0005725369,0.0005521503,0.0002642907],"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":[0.00003140769,0.00001165201,0.0003566661,0.0004711851,0.00001405094,0.00001281602,0.00001931992,0.0001294044,0.00009911956,0.0003999271,0.997109,0.001345413],"study_design_scores_gemma":[0.00008340002,0.000008054875,0.001654634,0.000158907,0.00001433365,0.00003164961,0.0000569384,0.0001817487,0.0002000472,0.0009856001,0.9966068,0.00001803012],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004153855,0.00002213082,0.00004640939,0.0000326122,0.00001004766,0.00000539774,0.9988407,0.0003760703,0.0006251517],"genre_scores_gemma":[0.0001730872,0.000031342,0.0002302636,0.00004757684,0.000003487759,0.00004918114,0.9987732,0.0001687726,0.0005231888],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8480341,"threshold_uncertainty_score":0.5083765,"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."}}