{"id":"W4416774020","doi":"10.1101/2025.11.22.25340800","title":"AI Clinical Decision Support System (CDSS) for Teleconsultations in eSanjeevani, India Telemedicine Service: A Prospective Implementation Study","year":2025,"lang":"","type":"preprint","venue":"medRxiv","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"All-India Institute of Medical Sciences; Ministry of Health and Family Welfare","keywords":"SNOMED CT; Triage; Telemedicine; Clinical decision support system; Decision support system; Health care; eHealth; Excellence; Limiting","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":[0.01480643,0.0005850588,0.000523155,0.001835109,0.001496235,0.002911458,0.001752174,0.001221691,0.004465401],"category_scores_gemma":[0.03255463,0.0007664969,0.001046199,0.002090889,0.001412326,0.002187393,0.002877394,0.003532261,0.0009856598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006329875,"about_ca_system_score_gemma":0.01324746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02370891,"about_ca_topic_score_gemma":0.02315693,"domain_scores_codex":[0.9886249,0.005829386,0.0009863288,0.0007521868,0.001756844,0.00205036],"domain_scores_gemma":[0.9692649,0.01243804,0.003704714,0.002350328,0.006391224,0.005850671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003699192,0.06183488,0.7225641,0.001912796,0.0003673012,0.001723632,0.03951721,0.002043396,0.002492773,0.001951983,0.008138509,0.1537542],"study_design_scores_gemma":[0.00200418,0.04566719,0.8574443,0.001019408,0.0005287275,0.0008515966,0.070664,0.007028186,0.002638194,0.0004050926,0.01146298,0.0002861968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960288,0.00008461234,0.0002989447,0.0004404492,0.00001918807,0.001400737,0.0004050233,0.00004223947,0.001279925],"genre_scores_gemma":[0.992183,0.0002578155,0.002875011,0.0009861619,0.00003200144,0.002355556,0.0006153642,0.0000219173,0.0006731444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02370891,"threshold_uncertainty_score":0.07830483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1331394436521363,"score_gpt":0.5357240568785883,"score_spread":0.4025846132264519,"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."}}