{"id":"W6924637566","doi":"10.15468/dl.w8ng5p","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Acupuncture Treatment Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); Identification (biology); Download","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":[0.0008536795,0.002127199,0.00143191,0.004236384,0.0009016297,0.002244822,0.002676386,0.001982711,0.1249849],"category_scores_gemma":[0.005421765,0.0007875684,0.001269603,0.007932119,0.0004356358,0.001952681,0.002296834,0.001893986,0.1816002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593961,"about_ca_system_score_gemma":0.002283243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02400211,"about_ca_topic_score_gemma":0.04153297,"domain_scores_codex":[0.9991346,0.0001270793,0.0001136811,0.000299705,0.0001890203,0.0001359639],"domain_scores_gemma":[0.9980863,0.000559689,0.0001798364,0.0004821201,0.0004812625,0.0002108323],"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":[0.00003650369,0.00001410939,0.0003918731,0.0005793658,0.00001614556,0.00001622253,0.00002464477,0.0001536933,0.0001265885,0.0003769522,0.9965258,0.001738067],"study_design_scores_gemma":[0.00008654766,0.0000110623,0.001855804,0.0001947243,0.00001601485,0.00004209055,0.00007040557,0.0002206681,0.0002097365,0.0008225192,0.9964522,0.00001820328],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005805126,0.00004122469,0.00005137218,0.00004432767,0.00001341923,0.000006961299,0.9985425,0.0005386783,0.0007033852],"genre_scores_gemma":[0.0001708179,0.00004363954,0.0002368855,0.00005007895,0.000003461569,0.00004226903,0.998823,0.0001383547,0.0004915288],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8750151,"threshold_uncertainty_score":0.418116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744445132571207,"score_gpt":0.2754382405872135,"score_spread":0.2579937892615014,"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."}}