{"id":"W6961914872","doi":"10.15468/dl.qyymy9","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); State (computer science); Confidentiality","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":[0.001031297,0.001950069,0.001490384,0.004402443,0.0009740354,0.002474568,0.002927843,0.002284547,0.1245021],"category_scores_gemma":[0.005771941,0.0007855282,0.001148269,0.00827256,0.0004568904,0.002092468,0.002300739,0.002169314,0.2008009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517564,"about_ca_system_score_gemma":0.002091986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01777333,"about_ca_topic_score_gemma":0.03248311,"domain_scores_codex":[0.9989703,0.0001643374,0.0001215122,0.0003550005,0.0002281638,0.0001607689],"domain_scores_gemma":[0.9975438,0.0006958795,0.0002298837,0.0006686925,0.0005888033,0.0002729777],"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":[0.00002684855,0.00001396588,0.000380171,0.0003768918,0.00001263113,0.00001380784,0.00001907131,0.0001420311,0.00008029696,0.0003667057,0.9972899,0.001277826],"study_design_scores_gemma":[0.00009537773,0.00001034454,0.002010496,0.0001705591,0.00001435795,0.00004088702,0.00007563573,0.0002613862,0.0001873397,0.001104211,0.9960105,0.00001883674],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005671782,0.00002953542,0.00005411933,0.00004601071,0.00001369009,0.000006426214,0.9987704,0.0003961957,0.0006268055],"genre_scores_gemma":[0.0001783694,0.00003011377,0.0002213542,0.00004695455,0.000004218404,0.000046303,0.9988735,0.0001172723,0.0004818332],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8754979,"threshold_uncertainty_score":0.4165009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03041304499061036,"score_gpt":0.1943999997252256,"score_spread":0.1639869547346152,"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."}}