{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009154135,0.002219416,0.0016344,0.004864326,0.0009207894,0.002331153,0.002914849,0.001983328,0.144291],"category_scores_gemma":[0.004808851,0.0008087808,0.001207937,0.008005884,0.0004477945,0.001973004,0.002637604,0.00181555,0.2556622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00158653,"about_ca_system_score_gemma":0.002209577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02266526,"about_ca_topic_score_gemma":0.04194429,"domain_scores_codex":[0.9991227,0.0001043873,0.00009654227,0.0002878899,0.0002197911,0.0001687243],"domain_scores_gemma":[0.9980597,0.0004254937,0.0001681443,0.0005335417,0.0005788747,0.0002343594],"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":[0.00002679059,0.000009454406,0.0002754886,0.0004198948,0.00001236414,0.00001186964,0.00001454588,0.0000932475,0.0001135846,0.0002525655,0.9972479,0.001522408],"study_design_scores_gemma":[0.00007230223,0.000008386929,0.001756073,0.0001856858,0.00001346946,0.00003904473,0.00005332193,0.0001637039,0.0002510611,0.0007128771,0.9967277,0.0000163838],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000393994,0.00003200638,0.00004586002,0.00002946222,0.00001128783,0.000006260324,0.99864,0.0005264038,0.0006692914],"genre_scores_gemma":[0.0001441337,0.00003344614,0.0002019128,0.00004295921,0.000003274993,0.00003859074,0.9989358,0.0001550323,0.0004447526],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.855709,"threshold_uncertainty_score":0.4827014,"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."}}