{"id":"W4396832512","doi":"10.1145/3613904.3642435","title":"GlucoMaker: Enabling Collaborative Customization of Glucose Monitors","year":2024,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; National Research Council Canada; Autodesk (Canada); University of Victoria","funders":"","keywords":"Personalization; Computer science; Function (biology); Human–computer interaction; Space (punctuation); Focus (optics); World Wide Web; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0002034232,0.000100411,0.0001163931,0.000443381,0.00006050388,0.0001098151,0.0003187395,0.00008457087,0.00004291188],"category_scores_gemma":[0.00007293214,0.00008818246,0.00003022442,0.00196654,0.00006115122,0.0008928947,0.0001143887,0.000160544,0.00009537215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008825272,"about_ca_system_score_gemma":0.00009076958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001212053,"about_ca_topic_score_gemma":0.000005452669,"domain_scores_codex":[0.9991357,0.00004440394,0.0002511821,0.000273846,0.0001604302,0.0001344855],"domain_scores_gemma":[0.9991267,0.0001025925,0.00007509397,0.0002663001,0.000413691,0.00001561373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008654342,0.00005385715,0.0002068729,0.00003742137,0.00006964526,0.00002221741,0.001627703,0.0001294765,0.09451553,0.86157,0.004358613,0.03740002],"study_design_scores_gemma":[0.0001386781,0.00008317077,0.0001810691,0.00007033976,0.00000623504,0.00001287394,0.0003081797,0.0766393,0.9041448,0.004144568,0.01413302,0.0001378037],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1552315,0.0004296147,0.8302047,0.001119801,0.001473316,0.0001982649,0.000002431897,0.0008203705,0.01052008],"genre_scores_gemma":[0.9775116,0.00002327261,0.02166982,0.00006407245,0.00005091736,0.00001529747,0.000002952991,0.000008488076,0.0006535563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8574254,"threshold_uncertainty_score":0.3595977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009123199178197823,"score_gpt":0.2724722690485573,"score_spread":0.2633490698703594,"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."}}