{"id":"W6924986599","doi":"10.15468/dl.v3qvjp","title":"Occurrence Download","year":2019,"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); State (computer science); Range (aeronautics); Reference data","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":[0.0007843404,0.002424241,0.001766061,0.005919963,0.001178709,0.003114561,0.002899473,0.002117781,0.173527],"category_scores_gemma":[0.006003385,0.0009498382,0.001568518,0.0102165,0.0004049713,0.003292624,0.003179975,0.001991014,0.2655312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001489838,"about_ca_system_score_gemma":0.002273028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02110529,"about_ca_topic_score_gemma":0.03244429,"domain_scores_codex":[0.9988554,0.0001401018,0.0001554775,0.0003981639,0.0002558415,0.0001949723],"domain_scores_gemma":[0.9977563,0.0005941473,0.0001904582,0.0006351947,0.0005679632,0.0002560579],"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":[0.00004378612,0.00001427855,0.0004536702,0.0005960299,0.00001613399,0.00002598201,0.00002811024,0.0001307306,0.0001260902,0.0003747099,0.9953277,0.002862682],"study_design_scores_gemma":[0.0000536213,0.00001189301,0.001579143,0.0001764852,0.00001477885,0.00006202515,0.0000879175,0.0003007939,0.0002079473,0.0008170282,0.9966694,0.00001898356],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001025276,0.00008121839,0.0001206759,0.00007483344,0.00003150673,0.00001078319,0.9964316,0.001806046,0.001340734],"genre_scores_gemma":[0.0002835474,0.00007119708,0.0003673954,0.00008133824,0.000007398465,0.00004792032,0.9978981,0.0004070551,0.0008361171],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.826473,"threshold_uncertainty_score":0.5805057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}