{"id":"W6961939445","doi":"10.15468/dl.ptfyjg","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Advances in Cucurbitaceae Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Set (abstract data type); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009666575,0.002307807,0.001803969,0.004785767,0.001067428,0.002727944,0.003154221,0.002454503,0.1270649],"category_scores_gemma":[0.005581571,0.0009277919,0.001298396,0.009369715,0.0004721642,0.00234306,0.002624958,0.002283881,0.200275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001827047,"about_ca_system_score_gemma":0.002415714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02226399,"about_ca_topic_score_gemma":0.03774609,"domain_scores_codex":[0.9989679,0.0001393322,0.0001300293,0.0003668529,0.0002331473,0.0001627249],"domain_scores_gemma":[0.9979457,0.0005694156,0.0001925762,0.0005303689,0.0005045963,0.0002572426],"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":[0.00003857391,0.00001519261,0.0004164586,0.0006169602,0.00001921318,0.00001838405,0.00002403965,0.0001643324,0.0001319308,0.0004101649,0.996663,0.001481737],"study_design_scores_gemma":[0.00009811823,0.000009341445,0.001828537,0.0002025629,0.00001677837,0.00004164949,0.00007189328,0.0002310836,0.000215669,0.0008690046,0.9963962,0.00001922452],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000469519,0.00003431797,0.00004575709,0.00003907866,0.00001140616,0.000005649435,0.9987495,0.0004594277,0.0006079374],"genre_scores_gemma":[0.0001527376,0.00003554205,0.0001983087,0.00004378088,0.000002856966,0.00003668101,0.9989999,0.0001356233,0.0003945899],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8729351,"threshold_uncertainty_score":0.4250745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01930414339031308,"score_gpt":0.2821610662610187,"score_spread":0.2628569228707056,"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."}}