{"id":"W2111937104","doi":"10.1177/002215540004800516","title":"Affinity Imaging of Red Blood Cells Using an Atomic Force Microscope","year":2000,"lang":"en","type":"article","venue":"Journal of Histochemistry & Cytochemistry","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":205,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Agarose; Lectin; Atomic force microscopy; Adhesion; Chemistry; Biophysics; Glycolipid; Cell adhesion; Materials science; Nanotechnology; Chromatography; Biochemistry; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001586577,0.0002398016,0.0001840167,0.0004205646,0.0003705095,0.0002714552,0.0003600398,0.0005394629,0.001279422],"category_scores_gemma":[0.0002846894,0.0001834928,0.0001270362,0.0001870717,0.0001466325,0.0003001109,0.0002778304,0.0004063205,0.0004289187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003808567,"about_ca_system_score_gemma":0.0001720568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002081778,"about_ca_topic_score_gemma":0.002465911,"domain_scores_codex":[0.999811,0.00001419974,0.000006540765,0.00003527652,0.00009715965,0.00003583253],"domain_scores_gemma":[0.9998484,0.00004963831,0.00001850327,0.00001455394,0.00004937717,0.00001954134],"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":[0.0000117808,0.000006433662,0.0001670575,0.00001334388,0.000001797933,0.00001853033,0.00001092324,0.00006892317,0.9968916,0.0001137462,0.00007343511,0.002622501],"study_design_scores_gemma":[0.00001367522,0.00008873571,0.006327414,0.000006589774,0.00001086735,0.0002612085,0.00003410011,0.01456514,0.9752017,0.0002073833,0.0032682,0.00001495007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8928736,0.001313689,0.09753896,0.0004691055,0.00006802243,0.0000686842,0.000295543,0.0009633951,0.006409039],"genre_scores_gemma":[0.9010991,0.0005863985,0.09370761,0.0001902708,0.00002865865,0.00007632721,0.000150665,0.0000513045,0.00410974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002081778,"threshold_uncertainty_score":0.00428009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007504419019490081,"score_gpt":0.2628314650184284,"score_spread":0.2553270459989383,"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."}}