{"id":"W2134763725","doi":"10.1369/0022155414554835","title":"New Automated Single-Cell Technique for Segmentation and Quantitation of Lipid Droplets","year":2014,"lang":"en","type":"article","venue":"Journal of Histochemistry & Cytochemistry","topic":"Lipid metabolism and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Thresholding; Segmentation; Lipid droplet; Computer science; Biological system; Image segmentation; Colocalization; Artificial intelligence; Organelle; Chemistry; Computer vision; Pattern recognition (psychology); Biology; Image (mathematics); Biochemistry; Cell biology","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":[0.0003678674,0.0002098205,0.0003300285,0.00004762595,0.00005786232,0.00001956825,0.0002211627,0.0002675262,0.00001330838],"category_scores_gemma":[0.0003052271,0.0002029343,0.0001683844,0.00007148457,0.00008052871,0.00001345038,0.00004472796,0.0001054576,4.188483e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000354319,"about_ca_system_score_gemma":0.0002045061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000206771,"about_ca_topic_score_gemma":3.38123e-7,"domain_scores_codex":[0.9986891,0.00002720934,0.0006389915,0.0002490682,0.0002127294,0.0001829216],"domain_scores_gemma":[0.998372,0.00005212911,0.0008386759,0.0002463018,0.0003321412,0.0001587951],"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":[0.0002265055,0.0001102071,0.0001161519,0.0004137057,0.00004172289,5.430243e-7,0.0000450352,0.000009788007,0.9919496,0.000002874422,0.005183368,0.001900514],"study_design_scores_gemma":[0.001082298,0.000268572,0.00005051338,0.00008801815,0.00009036058,0.00008841314,0.00008732162,0.00004541255,0.9867515,0.00002219877,0.01122203,0.0002033633],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9195923,0.001037945,0.07819124,0.00007144118,0.0001313899,0.0002482177,0.00002261831,0.00002208687,0.0006827371],"genre_scores_gemma":[0.9394932,0.00004328855,0.05907873,0.00003325918,0.0007675329,0.00001010299,0.00007206317,0.00002880204,0.0004730016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0199009,"threshold_uncertainty_score":0.8275419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00791821844036217,"score_gpt":0.2396043387144198,"score_spread":0.2316861202740576,"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."}}