{"id":"W6924809642","doi":"10.15468/dl.pbn5sc","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Advanced Semiconductor Detectors and Materials","field":"Engineering","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":[0.0008740433,0.00210179,0.001504075,0.004981589,0.001025003,0.002378311,0.002912878,0.002215569,0.1090329],"category_scores_gemma":[0.004312709,0.0007905859,0.001206986,0.008438534,0.0004779937,0.002144751,0.002317726,0.001979836,0.1762709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001570355,"about_ca_system_score_gemma":0.002031664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02086322,"about_ca_topic_score_gemma":0.03871467,"domain_scores_codex":[0.9991252,0.0001191423,0.0001027306,0.000314093,0.0001936616,0.0001451606],"domain_scores_gemma":[0.9980978,0.0005088849,0.0001810604,0.0005146066,0.0004746089,0.0002230016],"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":[0.00003527958,0.00001645002,0.0005505063,0.000560381,0.00001774794,0.0000201752,0.00002734316,0.0001906412,0.0001600122,0.0004288503,0.9962615,0.001731118],"study_design_scores_gemma":[0.00007119696,0.00001013102,0.002226056,0.0001817187,0.00001571855,0.00004715392,0.00008434586,0.0002313819,0.0002249377,0.0008594482,0.9960291,0.0000188734],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000688619,0.00003890237,0.00005680811,0.00003843411,0.00001395016,0.000005719153,0.998679,0.0004327639,0.0006655024],"genre_scores_gemma":[0.0001793648,0.0000338492,0.0002145507,0.00004224344,0.000003694691,0.00003398586,0.9989554,0.0001092785,0.0004275849],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8909671,"threshold_uncertainty_score":0.3647513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01235329755657029,"score_gpt":0.2038787595808255,"score_spread":0.1915254620242553,"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."}}