{"id":"W3091795721","doi":"10.1038/s41597-020-00690-0","title":"GalliForm, a database of Galliformes occurrence records from the Indo-Malay and Palaearctic, 1800–2008","year":2020,"lang":"en","type":"article","venue":"Scientific Data","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Zoological museum, Lomonosov Moscow State University; Lomonosov Moscow State University; Leverhulme Trust","keywords":"Macroecology; Database; Biodiversity; Geography; Species distribution; Ecology; Galliformes; Taxon; Biology; Habitat","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004122824,0.000567986,0.0003848842,0.01022552,0.0003742221,0.000523146,0.00068183,0.0002541414,0.009034391],"category_scores_gemma":[0.002726106,0.0002274854,0.0002696817,0.008073546,0.000350273,0.0008231304,0.00113408,0.0002613019,0.003676039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004646982,"about_ca_system_score_gemma":0.001100995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02044269,"about_ca_topic_score_gemma":0.04519466,"domain_scores_codex":[0.9996612,0.00002855241,0.000114825,0.00008026283,0.00008061618,0.00003450679],"domain_scores_gemma":[0.9977543,0.0002861724,0.001053071,0.0003312341,0.0003478403,0.0002274279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008836255,0.0001090611,0.556338,0.009025031,0.0006480771,0.001916575,0.006830854,0.001087817,0.01680468,0.002089503,0.1234384,0.2808284],"study_design_scores_gemma":[0.00001951293,0.00004631543,0.8118178,0.0003145952,0.0001369166,0.0009161421,0.0008258957,0.0004073262,0.001601048,0.0002498141,0.1836163,0.00004838439],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3265523,0.003299791,0.001957487,0.0001656934,0.00007156857,0.0002153175,0.6492995,0.0007830234,0.01765539],"genre_scores_gemma":[0.2908215,0.002618025,0.009426796,0.00007606352,0.00005706824,0.0004947054,0.6884494,0.0001531747,0.007903332],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02044269,"threshold_uncertainty_score":0.04064739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09181699789533744,"score_gpt":0.276527385229699,"score_spread":0.1847103873343616,"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."}}