{"id":"W2555661991","doi":"10.3791/54719","title":"Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins","year":2016,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Health Canada; National Institutes of Health","keywords":"Hemocytometer; Cell counting; Plug-in; Computer science; Sample (material); Bottleneck; Artificial intelligence; Counting process; Computer vision; Mathematics; Embedded system; Statistics; Pathology; Biology; Cell; Medicine; Chromatography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000320906,0.0001068863,0.0002987442,0.0003016502,0.00002974873,0.0000237562,0.0001217689,0.00006928342,0.00001842414],"category_scores_gemma":[0.0001117306,0.00007677514,0.0001653123,0.0002499016,0.00006576441,0.00001844174,0.00005095778,0.00002822404,3.128736e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002468408,"about_ca_system_score_gemma":0.00006170716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001483038,"about_ca_topic_score_gemma":0.000001992581,"domain_scores_codex":[0.9989638,0.0000672294,0.000505691,0.0001577511,0.0001932787,0.0001122167],"domain_scores_gemma":[0.998705,0.00001455542,0.0007518979,0.0001750415,0.0003113074,0.00004225188],"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":[0.00007745733,0.0001151784,0.006123527,0.00001411168,0.0005492745,0.000001852983,0.00008277074,0.000007810873,0.9926137,0.000003021751,0.0002819087,0.0001294348],"study_design_scores_gemma":[0.0005524657,0.0001022988,0.002260731,0.00003977205,0.0005171723,0.000007261273,0.00008190004,0.001761441,0.9943565,0.000003340528,0.0002251519,0.00009201604],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778469,0.0007811246,0.02120924,0.000009187887,0.00001306941,0.00005801116,0.000003098721,0.00001149267,0.00006789415],"genre_scores_gemma":[0.9914984,0.0003355738,0.008038347,0.00002892171,0.00002802551,0.000001530027,0.000008643702,0.00001323231,0.00004738526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01365146,"threshold_uncertainty_score":0.3130799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016451812923972,"score_gpt":0.413901170594951,"score_spread":0.3937366524657112,"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."}}