{"id":"W6924861826","doi":"10.15468/dl.ymczgs","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Listing (finance); Range (aeronautics)","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":[0.0007065297,0.0002733828,0.0002817985,0.0001520069,0.0003278012,0.0005359123,0.001796222,0.000300666,0.00009211848],"category_scores_gemma":[0.0002709748,0.0002775868,0.0001702158,0.0008276167,0.0001045749,0.002102509,0.001030663,0.00031257,0.5423741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002165944,"about_ca_system_score_gemma":0.0001956616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005910475,"about_ca_topic_score_gemma":0.000005686908,"domain_scores_codex":[0.9981392,0.0001538612,0.0003818464,0.0003170535,0.0006453346,0.0003626761],"domain_scores_gemma":[0.9983247,0.00005854159,0.0002583274,0.000912864,0.0002865038,0.0001590783],"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":[0.00001277246,0.00001446225,0.00002766778,0.00008177717,0.00001733591,0.00001061259,0.00003779681,0.00000970128,6.461791e-8,5.789901e-7,0.9933541,0.006433129],"study_design_scores_gemma":[0.0003193217,0.00002967499,0.00004656038,0.0000031495,0.00001784766,0.000007226171,0.00001732412,0.000003326215,0.000005529764,0.00001112225,0.9992461,0.000292831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001146805,0.00001304896,0.004747014,0.0002317304,0.001438702,0.0001941516,0.9929361,0.0003498146,0.00007802125],"genre_scores_gemma":[4.096875e-7,0.00004134182,0.00009186297,0.0006990951,0.000001901096,0.000002577229,0.9991624,1.11705e-8,4.174439e-7],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.542282,"threshold_uncertainty_score":0.9999676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02594724913233596,"score_gpt":0.2548778658797619,"score_spread":0.2289306167474259,"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."}}