{"id":"W2762499814","doi":"10.1615/critrevbiomedeng.2017021231","title":"Preface: McMaster Research Highlights","year":2016,"lang":"en","type":"article","venue":"Critical Reviews in Biomedical Engineering","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Medical physics; 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":[0.001409637,0.0001409285,0.0002557849,0.000163264,0.00002519526,0.00001823612,0.0002942678,0.0001875846,0.0002239925],"category_scores_gemma":[0.005357769,0.00008938182,0.0001010126,0.0003155365,0.0002559875,0.000007522634,0.0002149636,0.0001821565,0.0001174777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004212103,"about_ca_system_score_gemma":0.00002182903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002508566,"about_ca_topic_score_gemma":0.000001628993,"domain_scores_codex":[0.998315,0.0001225501,0.0004015475,0.0004083676,0.0002827979,0.0004697446],"domain_scores_gemma":[0.9991558,0.0001622137,0.00001405914,0.0003832102,0.00007223054,0.0002125039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000656049,0.00007028451,0.00004089158,0.0001159872,0.00000748264,0.00001598366,0.000005683745,2.209139e-7,0.940771,0.001236689,0.01280981,0.04491938],"study_design_scores_gemma":[0.000148354,0.00008811108,0.0001045867,0.0004104845,0.000005769617,0.000007176849,0.000001623424,0.00007983432,0.1013409,0.0001313144,0.8975375,0.0001443535],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1167313,0.1151863,0.7180063,0.02611592,0.0007990253,0.003172716,0.00002603385,0.0005069922,0.01945535],"genre_scores_gemma":[0.9665071,0.01825109,0.0120139,0.000319281,0.0007468399,0.0002700857,0.00001863665,0.00005945286,0.001813581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8847277,"threshold_uncertainty_score":0.6414137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03273355791151501,"score_gpt":0.3704133434426017,"score_spread":0.3376797855310867,"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."}}