{"id":"W6887156998","doi":"10.15468/dl.r8ogiv","title":"Occurrence Download","year":2018,"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); Range (aeronautics); China; Feature (linguistics)","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":[0.0007953429,0.003024131,0.002220743,0.007717804,0.001223047,0.003548007,0.00234829,0.002566847,0.2588502],"category_scores_gemma":[0.006243179,0.0009791339,0.002051479,0.01098943,0.0004199714,0.003608002,0.003479677,0.002100463,0.3164883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414425,"about_ca_system_score_gemma":0.002938293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02424856,"about_ca_topic_score_gemma":0.03804055,"domain_scores_codex":[0.9987692,0.0001420349,0.0001895529,0.000417973,0.0002619073,0.0002192675],"domain_scores_gemma":[0.9975098,0.0007443299,0.0001996726,0.0005858414,0.0005999313,0.0003603582],"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":[0.00006001801,0.0000211106,0.0003966211,0.0008463651,0.00001980296,0.0000328182,0.0000376642,0.0001980831,0.0001251709,0.0005327158,0.9936615,0.004068044],"study_design_scores_gemma":[0.00009145726,0.00001522088,0.001339767,0.0002455449,0.00002016603,0.00006210626,0.0001100172,0.0004114815,0.000179821,0.001400011,0.9960976,0.00002679339],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000937379,0.00009782297,0.0001333128,0.0000787679,0.00004165358,0.00001641751,0.9956173,0.001857855,0.002063209],"genre_scores_gemma":[0.00031913,0.0001190036,0.0006671394,0.0001107768,0.00001184161,0.00006607669,0.9969818,0.0004145597,0.00130972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7411498,"threshold_uncertainty_score":0.8659402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881883250631837,"score_gpt":0.2330296220854826,"score_spread":0.2142107895791642,"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."}}