{"id":"W4281853452","doi":"10.1021/acsami.2c05071","title":"Hydrogel Stamping for Rapid, Multiplexed, Point-of-Care Immunostaining of Cells and Tissues","year":2022,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ministry of Science and ICT, South Korea; Massachusetts General Hospital","keywords":"Immunostaining; Materials science; Biomedical engineering; Multiplexing; Staining; Stamping; Fluorescence; Pathology; Computer science; Nanotechnology; Immunohistochemistry; Medicine; Optics","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":[0.000439805,0.0004448532,0.0002712508,0.0003788849,0.000221178,0.0002319859,0.0004297464,0.0002977682,0.001880606],"category_scores_gemma":[0.0004436019,0.000252023,0.0002971406,0.0002450555,0.0003064341,0.0003618194,0.0002675078,0.0004818357,0.0005487791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004070309,"about_ca_system_score_gemma":0.0002902914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003263944,"about_ca_topic_score_gemma":0.001176708,"domain_scores_codex":[0.9996756,0.00004241459,0.00002788873,0.00007600055,0.0001424646,0.00003567751],"domain_scores_gemma":[0.9997236,0.00009580829,0.00007691661,0.00004094011,0.00003361228,0.00002919049],"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":[0.0000179044,0.000006846746,0.00008905709,0.00007042409,0.000004539168,0.00003657475,0.00001429447,0.0001270112,0.9936876,0.000247634,0.0001776467,0.005520585],"study_design_scores_gemma":[0.000006550623,0.00007074552,0.0005937532,0.000005708402,0.00001059681,0.0001517225,0.000007246468,0.00343991,0.9917799,0.00007192088,0.003852658,0.000009260873],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4013108,0.01115551,0.5746171,0.000740105,0.0006835876,0.0004547444,0.001252564,0.00224039,0.007545121],"genre_scores_gemma":[0.6196649,0.004783344,0.3696506,0.000263978,0.0001750378,0.0003993947,0.0006458524,0.0001326808,0.004284081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001880606,"threshold_uncertainty_score":0.00629127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009188262779992965,"score_gpt":0.2609400845429141,"score_spread":0.2517518217629211,"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."}}