{"id":"W3150910430","doi":"10.1101/2021.03.28.437430","title":"Maxent modeling for predicting the potential distribution of global <i>talaromycosis</i>","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Fungal Infections and Studies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Guangxi Medical University; National Natural Science Foundation of China","keywords":"Geography; Environmental niche modelling; Distribution (mathematics); Ecology; China; Ecological niche; Population; Quarter (Canadian coin); Peninsula; Physical geography; Environmental health; Habitat; Biology; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001305687,0.001073042,0.0007752369,0.001111714,0.0005580955,0.001201314,0.001135994,0.001050441,0.002575862],"category_scores_gemma":[0.001822772,0.0004143244,0.001589108,0.0007221434,0.0004574254,0.0006623899,0.0006903464,0.0009546516,0.0003269833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009482941,"about_ca_system_score_gemma":0.0009542066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02012464,"about_ca_topic_score_gemma":0.0114603,"domain_scores_codex":[0.999622,0.0001541519,0.00001839585,0.00009524514,0.00003352704,0.00007679906],"domain_scores_gemma":[0.9992225,0.0005326259,0.00007143027,0.00001891916,0.0001044894,0.00005001582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006556192,0.0000571964,0.01494136,0.00003939206,0.00007322266,0.0001146003,0.00004000888,0.973586,0.0005286204,0.001115212,0.0007594195,0.008679387],"study_design_scores_gemma":[0.000001889199,0.000008466901,0.0006373447,0.000003368292,0.000005815349,0.000008611783,0.00001219308,0.9986811,0.0000763513,0.0004301992,0.0001313346,0.000003298799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6808358,0.001395741,0.3077099,0.001598087,0.0001587477,0.0001058092,0.001901038,0.0009759019,0.00531905],"genre_scores_gemma":[0.9812053,0.000220695,0.01547479,0.0001443895,0.00003683627,0.00007214476,0.0009027419,0.00004648377,0.001896687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02012464,"threshold_uncertainty_score":0.04001498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455589201750551,"score_gpt":0.2372267080733761,"score_spread":0.2226708160558706,"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."}}