{"id":"W2410507446","doi":"10.1021/acsami.5b02404","title":"In Situ Electrochemical ELISA for Specific Identification of Captured Cancer Cells","year":2015,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"Circulating tumor cell; Cancer cell; Cancer; Materials science; In situ; Cancer research; Molecular biology; Biology; Metastasis; Medicine; Internal medicine; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008792857,0.001012367,0.0005134784,0.0006123643,0.0002726463,0.0005157681,0.001065164,0.001304849,0.001974956],"category_scores_gemma":[0.001051148,0.0004613599,0.0003563456,0.0004014297,0.0002588508,0.0005370562,0.0005522954,0.001207505,0.001008977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003389623,"about_ca_system_score_gemma":0.0002931749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003446635,"about_ca_topic_score_gemma":0.0007481841,"domain_scores_codex":[0.9987704,0.0003139171,0.00009115578,0.0003160137,0.000398222,0.0001101365],"domain_scores_gemma":[0.9994836,0.000256033,0.00006279314,0.00004775292,0.0001086839,0.00004112785],"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":[0.00001660727,0.00003727113,0.0001100828,0.00006535918,0.000006754837,0.0000279374,0.00002321275,0.00007197577,0.996143,0.0001477849,0.000154297,0.003195693],"study_design_scores_gemma":[0.000006285117,0.0001080018,0.0004201045,0.000009090774,0.0000136511,0.000198296,0.00001901316,0.004188071,0.9919165,0.00009224063,0.003019001,0.000009890074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3066387,0.01030375,0.670425,0.001046585,0.001057974,0.000413048,0.0009504803,0.001809201,0.007355264],"genre_scores_gemma":[0.6297605,0.007802808,0.347067,0.001074466,0.0002916173,0.000622774,0.0008730497,0.000109599,0.01239816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001974956,"threshold_uncertainty_score":0.006606936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01769180344247112,"score_gpt":0.2365242611272631,"score_spread":0.218832457684792,"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."}}