{"id":"W6905871904","doi":"10.15468/dl.q2py2g","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Range (aeronautics); Identification (biology); Order (exchange)","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":[0.0008833926,0.001889631,0.001564045,0.004909399,0.0009274733,0.00253775,0.00265481,0.001923043,0.1733746],"category_scores_gemma":[0.005550572,0.0009107079,0.001085037,0.009639855,0.0003983017,0.002269719,0.002333808,0.001785233,0.2317059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001509605,"about_ca_system_score_gemma":0.002189553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01950623,"about_ca_topic_score_gemma":0.0336502,"domain_scores_codex":[0.9990208,0.0001311873,0.0001291348,0.0003525162,0.0002017221,0.0001646824],"domain_scores_gemma":[0.9977417,0.0006233593,0.0002271208,0.0005544436,0.000600361,0.0002528909],"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":[0.00003205922,0.00001059979,0.0003925063,0.0005930204,0.00001467491,0.0000141399,0.00002029811,0.0001200173,0.0001184229,0.0003900668,0.9968232,0.001470943],"study_design_scores_gemma":[0.00006778022,0.000008427959,0.001769378,0.0001918184,0.00001433607,0.00003275428,0.00005623982,0.0001273491,0.0001706965,0.0007719219,0.9967716,0.00001757957],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003665402,0.00002586597,0.0000366153,0.00002900274,0.00001005764,0.000004335097,0.9989609,0.0002688934,0.0006277791],"genre_scores_gemma":[0.0001578161,0.00003589471,0.0001821037,0.0000462939,0.000003574772,0.00003975592,0.9988503,0.0001288137,0.0005554343],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8266254,"threshold_uncertainty_score":0.5799959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}