{"id":"W2056119981","doi":"10.1021/nn302917e","title":"Array-Based Sensing of Metastatic Cells and Tissues Using Nanoparticle–Fluorescent Protein Conjugates","year":2012,"lang":"en","type":"article","venue":"ACS Nano","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Bone and Joint Health Institute; University of Calgary","funders":"National Institute of General Medical Sciences","keywords":"Analyte; Cancer cell; Proteome; Intracellular; Metastasis; Cancer; Fluorescence; Cancer research; Biomedical engineering; Nanotechnology; Computational biology; Biology; Pathology; Chemistry; Materials science; Cell biology; Bioinformatics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002223051,0.0001367897,0.0002191057,0.00004476763,0.0000580848,0.00001359491,0.00004933424,0.0000613044,9.143762e-7],"category_scores_gemma":[0.00005439241,0.0001115908,0.00005791313,0.00009025164,0.0001406897,0.000006660387,0.00003652701,0.00003738575,8.018968e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000824525,"about_ca_system_score_gemma":0.00002462244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002261217,"about_ca_topic_score_gemma":0.000003847229,"domain_scores_codex":[0.9991821,0.00007633414,0.0002213669,0.0001806809,0.0001053712,0.0002341185],"domain_scores_gemma":[0.9994856,0.00001313364,0.0001374668,0.0002149554,0.00007999577,0.00006888767],"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":[0.00005573947,0.00005751038,0.0004081332,0.0000316332,0.00004211077,8.594163e-7,0.00002294567,0.000005874605,0.998206,0.00001065573,0.00001870579,0.001139866],"study_design_scores_gemma":[0.0003378649,0.0001126062,0.00002311184,0.00005212168,0.0000813149,0.000006835246,0.00005033736,0.0001227564,0.9983885,0.00002636587,0.0006555234,0.0001426986],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996381,0.0007999131,0.002513586,0.00003519473,0.00002747932,0.0001965527,0.000008718229,0.00001808303,0.00001946979],"genre_scores_gemma":[0.9391982,0.00003075956,0.06059785,0.00006335791,0.00004796621,0.000001691495,0.00001194478,0.00001502275,0.00003319111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05808427,"threshold_uncertainty_score":0.455054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675671911058053,"score_gpt":0.2770921534933078,"score_spread":0.2603354343827273,"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."}}