{"id":"W1998695812","doi":"10.1371/journal.pone.0009396","title":"High Resolution Niche Models of Malaria Vectors in Northern Tanzania: A New Capacity to Predict Malaria Risk?","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Malaria Research and Control","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Canadian Armed Forces","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Malaria; Vector (molecular biology); Anopheles gambiae; Anopheles; Land cover; Mosquito control; Ecology; Geography; Ecological niche; Habitat; Niche; Environmental niche modelling; Plasmodium falciparum; Biology; Land use","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006460375,0.0001825843,0.0005388222,0.0002496675,0.00004713047,0.00001699593,0.0002164225,0.0002456349,0.0003258219],"category_scores_gemma":[0.001383071,0.0001645833,0.00008550269,0.0004011575,0.00006151822,0.0001257004,0.00008396665,0.001007332,0.00006029224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009481661,"about_ca_system_score_gemma":0.0003036192,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009059863,"about_ca_topic_score_gemma":0.01386045,"domain_scores_codex":[0.9978168,0.0001236355,0.0004177712,0.0003667971,0.0007859795,0.0004890336],"domain_scores_gemma":[0.998395,0.000102099,0.0001174761,0.0006317721,0.0002599051,0.0004937873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.004053783,0.003495968,0.3257653,0.0002626712,0.0006637888,0.00005068974,0.0008192913,0.0002976919,0.6464573,0.01700266,0.0004425856,0.000688324],"study_design_scores_gemma":[0.006940738,0.001330973,0.9323727,0.0003601641,0.0004426883,0.000007687743,0.00003491857,0.03091897,0.02241223,0.004852675,0.00005302752,0.0002732326],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902604,0.0000614693,0.00111183,0.006032832,0.00007119589,0.001346197,0.00007255182,0.00006176344,0.0009817464],"genre_scores_gemma":[0.99198,0.00002388241,0.006838251,0.0001012995,0.0003288487,0.00008124328,0.00001783198,0.00003340967,0.0005952272],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6240451,"threshold_uncertainty_score":0.9975389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03400069823185237,"score_gpt":0.2347819475740693,"score_spread":0.2007812493422169,"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."}}