{"id":"W3166259992","doi":"10.1049/pbhe026e_ch14","title":"Biosensors in healthcare: an overview","year":2020,"lang":"en","type":"book-chapter","venue":"IET eBooks","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Biosensor; Respiratory monitoring; Nanotechnology; Computer science; Biomedical engineering; Medicine; Materials science; Respiratory system; Internal 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":[0.001747244,0.001476837,0.001532605,0.002496674,0.0007374781,0.00301196,0.001622281,0.003900556,0.006240384],"category_scores_gemma":[0.001226359,0.000739542,0.0009837741,0.002802354,0.001121901,0.004056189,0.002014849,0.003676795,0.008753374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001352536,"about_ca_system_score_gemma":0.001293899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007520345,"about_ca_topic_score_gemma":0.0006776262,"domain_scores_codex":[0.9981576,0.0003613885,0.000120907,0.0002568983,0.0009619883,0.0001412684],"domain_scores_gemma":[0.9993924,0.0002332335,0.00004070251,0.00003625874,0.0002428362,0.00005453162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001076547,0.0001805612,0.0003671597,0.0105399,0.00008638545,0.0003975243,0.0002957188,0.001230962,0.01158327,0.04502225,0.07780895,0.8523797],"study_design_scores_gemma":[0.000006342307,0.0001286548,0.0001673051,0.001090962,0.00001583894,0.00094042,0.00007015486,0.0004576678,0.001858768,0.008348426,0.9868846,0.00003094334],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003895299,0.9739041,0.009012749,0.002670769,0.002523159,0.00004981506,0.00005550397,0.0001538127,0.0112406],"genre_scores_gemma":[0.003775307,0.9735475,0.009133432,0.001941125,0.002376988,0.0001093084,0.0001243973,0.00003993308,0.00895199],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006240384,"threshold_uncertainty_score":0.02087623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03808851189174633,"score_gpt":0.2435620120562876,"score_spread":0.2054735001645412,"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."}}