{"id":"W6924796891","doi":"10.15468/dl.agyb6z","title":"Occurrence Download","year":2020,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Hydropower, Displacement, Environmental Impact","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Range (aeronautics); Danaus; 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":[0.0009621387,0.001814988,0.001490591,0.005098875,0.0008356372,0.002271206,0.002662808,0.001902354,0.1486318],"category_scores_gemma":[0.005493361,0.0008638173,0.001070599,0.01118572,0.0004220717,0.001891538,0.002130932,0.00176238,0.1752877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001716543,"about_ca_system_score_gemma":0.002521724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03032828,"about_ca_topic_score_gemma":0.04418508,"domain_scores_codex":[0.9990652,0.0001173852,0.0001276002,0.0003046832,0.0002195221,0.0001656453],"domain_scores_gemma":[0.9978063,0.0005935699,0.0002361333,0.0005030788,0.0005834103,0.0002775138],"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":[0.0000318269,0.0000105751,0.0004115836,0.0005443585,0.00001671961,0.00001492104,0.00002146976,0.000156247,0.00009853238,0.0003844078,0.9969644,0.001344846],"study_design_scores_gemma":[0.00009785776,0.000008174276,0.002489178,0.0001955541,0.00001726029,0.00003647852,0.00007268906,0.0001879836,0.0001869955,0.0007420144,0.9959467,0.00001912803],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003132368,0.00001750231,0.00002779535,0.00002525655,0.000007805444,0.00000364607,0.9992771,0.0002001792,0.0004095304],"genre_scores_gemma":[0.0001515687,0.00002755215,0.000142206,0.00003473872,0.000002806851,0.00003459867,0.9991344,0.00009224192,0.0003799806],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8513682,"threshold_uncertainty_score":0.497223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168052018853231,"score_gpt":0.3205801505108544,"score_spread":0.2988996303223221,"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."}}