{"id":"W2611590119","doi":"10.29011/2577-2260.100001","title":"Smartphone-Enabled Biotelemetric System for A Smart Contact Lens","year":2018,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics Open Access","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Contact lens; Lens (geology); Computer science; Human–computer interaction; Embedded system; Optometry; Optics; Medicine; Ophthalmology; Physics","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":[0.0003384671,0.0006516498,0.0006333816,0.0006832842,0.000307419,0.0007868921,0.0009756479,0.00105356,0.01852501],"category_scores_gemma":[0.0007873234,0.0002525055,0.0003367357,0.0003984018,0.000187329,0.0008762736,0.001127823,0.0005717466,0.008150487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00034973,"about_ca_system_score_gemma":0.0005528192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001009754,"about_ca_topic_score_gemma":0.001728904,"domain_scores_codex":[0.9993728,0.00007382099,0.00004873257,0.0001388762,0.0003160002,0.00004985551],"domain_scores_gemma":[0.9995624,0.00005637862,0.00004504684,0.00007347935,0.0001929774,0.00006963391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008595776,0.0002065824,0.005135934,0.0007007254,0.00008063381,0.0013098,0.0004004264,0.0002675588,0.7451473,0.002888105,0.0224753,0.220528],"study_design_scores_gemma":[0.0004320577,0.002531991,0.04307776,0.0003226096,0.0003366618,0.02205095,0.0003662488,0.04375537,0.4984028,0.001704807,0.3866025,0.0004161871],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1890319,0.007955518,0.6933345,0.002934357,0.002002092,0.002421146,0.005548532,0.03766031,0.05911171],"genre_scores_gemma":[0.6341382,0.002603444,0.2717661,0.002698898,0.0005541549,0.001149387,0.002202728,0.0004484719,0.08443864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01852501,"threshold_uncertainty_score":0.06197232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07294473899450768,"score_gpt":0.3487635390069626,"score_spread":0.275818800012455,"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."}}