{"id":"W6905939404","doi":"10.15468/dl.k0epox","title":"Occurrence Download","year":2015,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Real world data; Data set","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003375983,0.0003021952,0.0002658924,0.000127169,0.0002594869,0.0004746616,0.002379677,0.0003356787,0.0005617962],"category_scores_gemma":[0.0001685434,0.000317372,0.0001374511,0.0005832656,0.00009853172,0.004309464,0.001374776,0.0004044247,0.4129717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006848876,"about_ca_system_score_gemma":0.0004032913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008139178,"about_ca_topic_score_gemma":0.00003527903,"domain_scores_codex":[0.9980472,0.00008228107,0.0004381316,0.0003184552,0.0007828224,0.0003311631],"domain_scores_gemma":[0.997263,0.00003021754,0.0003977723,0.001244839,0.0007938875,0.0002702675],"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":[0.00000912897,0.00003367749,0.000101992,0.00005300671,0.00002071697,0.0000028408,0.00008500673,0.00001836795,9.689689e-9,7.591867e-7,0.9983065,0.001368037],"study_design_scores_gemma":[0.000199797,0.00003500447,0.00001777426,0.000002717843,0.00002018879,0.00001716709,0.00008108675,0.000004483438,0.00000120204,0.00000778138,0.9993083,0.0003045272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002746935,0.00001429676,0.0005297994,0.0005658843,0.001771788,0.0002386266,0.9962937,0.0002389037,0.000319571],"genre_scores_gemma":[0.000003760889,0.0000187803,0.00003769563,0.001093608,0.000002160507,0.000004457965,0.9988394,8.781163e-9,1.571113e-7],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4124099,"threshold_uncertainty_score":0.9999278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02309041815667848,"score_gpt":0.2452501109550816,"score_spread":0.2221596927984031,"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."}}