{"id":"W4298864966","doi":"","title":"Estimation of polydispersity in aggregating red blood cells by quantitative ultrasound backscatter analysis","year":2018,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Blood properties and coagulation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Backscatter (email); Dispersity; Ultrasound; Quantitative analysis (chemistry); Computer science; Materials science; Remote sensing; Biological system; Chromatography; Geology; Chemistry; Medicine; Radiology; Biology; Telecommunications; Polymer chemistry","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":[0.001107495,0.0003196729,0.0003994394,0.001576734,0.0002236839,0.0005798747,0.0002571981,0.0005116243,0.001390299],"category_scores_gemma":[0.001290415,0.0002514655,0.000238441,0.0005930083,0.0003261241,0.0003780604,0.0003533803,0.0004624938,0.000628891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002450403,"about_ca_system_score_gemma":0.0001607658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004169031,"about_ca_topic_score_gemma":0.0005082905,"domain_scores_codex":[0.9993974,0.0001579899,0.00004313745,0.0001266435,0.0002268771,0.00004803307],"domain_scores_gemma":[0.9987479,0.0006354026,0.0002138522,0.00006038078,0.0002863479,0.00005605471],"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":[0.0001014301,0.00002427273,0.002066558,0.00004315131,0.00001420953,0.00002100664,0.00006005066,0.0001083156,0.9896907,0.00008847448,0.00003897534,0.007743036],"study_design_scores_gemma":[0.00001378469,0.0004859917,0.04106894,0.00001864425,0.0001007974,0.0005218399,0.0001375064,0.01000358,0.9461475,0.0002784193,0.001179811,0.00004328276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8795099,0.004829656,0.1127271,0.0001466017,0.00007282865,0.00009311249,0.0002890903,0.0002608704,0.002070779],"genre_scores_gemma":[0.9070898,0.00347096,0.08522652,0.0002486501,0.0001012439,0.0001524424,0.0003797043,0.00008970502,0.003241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001576734,"threshold_uncertainty_score":0.00585711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0110852979374504,"score_gpt":0.2351494809069764,"score_spread":0.224064182969526,"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."}}