{"id":"W2803753420","doi":"10.1016/j.bios.2018.05.043","title":"Nano-biosensor for highly sensitive detection of HER2 positive breast cancer","year":2018,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":152,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Iran University of Science and Technology; University of Calgary","keywords":"Biosensor; Nanocomposite; Materials science; Nanotechnology; Detection limit; Nanomaterials; Nanoparticle; Electrode; Colloidal gold; Linear range; Polyaniline; Surface modification; Polymer; Chemistry; Chromatography; Polymerization","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001527895,0.0002427617,0.0002656106,0.00008716074,0.0001803115,0.00001916991,0.00007766693,0.0002524781,4.865819e-7],"category_scores_gemma":[0.00003257793,0.0002032321,0.0001485704,0.0001908948,0.0003934677,0.000006472348,0.00005081977,0.00007327245,6.629365e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003820064,"about_ca_system_score_gemma":0.00006622006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007654728,"about_ca_topic_score_gemma":0.0003215788,"domain_scores_codex":[0.9987099,0.00005121563,0.000256038,0.0004904359,0.0001127539,0.000379701],"domain_scores_gemma":[0.9989464,0.00002190646,0.0001936385,0.0002260641,0.0005358466,0.00007614947],"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":[0.0005300444,0.00005271809,0.0001018924,0.00001608778,0.0001395694,5.77618e-7,0.00002322065,3.579548e-7,0.9828801,0.0001272125,0.0001458328,0.01598243],"study_design_scores_gemma":[0.0003875997,0.001615034,0.0009964231,0.00002960576,0.0001004916,0.00006126011,0.00007263732,0.0001792117,0.9920064,0.00006693175,0.004199829,0.0002846186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964367,0.0004028964,0.001773619,0.0003904003,0.00009142922,0.0003133229,0.000481771,0.0000386831,0.00007118704],"genre_scores_gemma":[0.9960517,0.0009776214,0.001905611,0.0002303914,0.0004645912,0.00001063191,0.00006661922,0.0000302738,0.0002625485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01569782,"threshold_uncertainty_score":0.8287565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005362615471612709,"score_gpt":0.2580370079979506,"score_spread":0.2526743925263379,"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."}}