{"id":"W4408101337","doi":"10.52015/nijec.v3i2.79","title":"Med Box: Smart Medication Reminding & Monitoring","year":2025,"lang":"en","type":"article","venue":"NUML International Journal of Engineering and Computing","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; Nexen (Canada)","funders":"","keywords":"Computer science; Medicine","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":[0.0005260858,0.001047941,0.0009204829,0.001053024,0.0004897124,0.0009773611,0.001098586,0.001432123,0.133699],"category_scores_gemma":[0.002890175,0.0004436209,0.0003797833,0.0004621355,0.00016532,0.0008976772,0.001097334,0.0007235697,0.05227285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001634681,"about_ca_system_score_gemma":0.0003549991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003575984,"about_ca_topic_score_gemma":0.0004341457,"domain_scores_codex":[0.9993356,0.0001216174,0.00008553942,0.0001494027,0.000251105,0.00005666139],"domain_scores_gemma":[0.9978957,0.0008065698,0.0003284184,0.000318899,0.0004232659,0.0002271151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001810139,0.0005181578,0.01286151,0.001235564,0.00006536372,0.001060774,0.0003056596,0.0003626599,0.0149182,0.001330947,0.4927918,0.4727392],"study_design_scores_gemma":[0.0008096847,0.001530877,0.04300711,0.001264367,0.0002100444,0.005584944,0.0002700959,0.01293533,0.04860285,0.002402082,0.8831295,0.0002531015],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1098849,0.009409648,0.1271506,0.01164105,0.006676055,0.006721195,0.06561159,0.3074022,0.3555028],"genre_scores_gemma":[0.5364915,0.00444311,0.1147939,0.01717278,0.003591357,0.004045999,0.01724157,0.005179578,0.2970403],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.133699,"threshold_uncertainty_score":0.4472677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.022867907823447,"score_gpt":0.3272519814772104,"score_spread":0.3043840736537634,"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."}}