{"id":"W7133054359","doi":"","title":"Quantifying Diarrheal Characteristics: A Computer Vision Approach for Global Health","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"","keywords":"Diarrhea; Diarrheal disease; Diarrheal diseases; Traveler's diarrhea; Global health; Public health","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007475049,0.001107291,0.001468172,0.0002591682,0.0009841158,0.0003730406,0.000676387,0.0004698079,0.0001937468],"category_scores_gemma":[0.00009772707,0.001404093,0.0005284806,0.0006853632,0.00004409331,0.0002584367,0.000227958,0.00103936,0.00003986032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00264523,"about_ca_system_score_gemma":0.0004767691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005541188,"about_ca_topic_score_gemma":0.00005987464,"domain_scores_codex":[0.9949636,0.0002238385,0.001183767,0.001329897,0.0008082194,0.001490619],"domain_scores_gemma":[0.9975035,0.0003689261,0.0007198384,0.0007048502,0.0001854282,0.000517414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004870466,0.00330302,0.02764644,0.1059719,0.004270013,0.0002279573,0.09220131,0.0807265,0.06302899,0.01966733,0.01303372,0.5850524],"study_design_scores_gemma":[0.01372802,0.01238648,0.08620603,0.008763573,0.001526972,0.0003097658,0.038431,0.7862594,0.004736584,0.0009229978,0.0309147,0.01581444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1297611,0.005876125,0.8326249,0.0003764888,0.02157206,0.005874751,0.0007369514,0.0007254956,0.002452119],"genre_scores_gemma":[0.9004651,0.0007360309,0.08353849,0.0001077217,0.00442973,0.0009473615,0.008486865,0.0004889455,0.0007997283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.770704,"threshold_uncertainty_score":0.9988409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03428280395020355,"score_gpt":0.3727048864910913,"score_spread":0.3384220825408877,"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."}}