{"id":"W2109576862","doi":"10.1109/iembs.2008.4649168","title":"Watershed deconvolution for cell segmentation","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Segmentation; Deconvolution; Computer science; Boundary (topology); Artificial intelligence; Image segmentation; Computer vision; Matching (statistics); Pattern recognition (psychology); Algorithm; Mathematics","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":[0.0008272624,0.0005844373,0.001010754,0.001006271,0.0005362915,0.001020956,0.001037507,0.001603348,0.004266877],"category_scores_gemma":[0.001915686,0.0005275295,0.0008537336,0.001152903,0.001069196,0.001341046,0.001404552,0.001469414,0.002054767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001182653,"about_ca_system_score_gemma":0.001485869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002540914,"about_ca_topic_score_gemma":0.002434353,"domain_scores_codex":[0.9995306,0.00008169155,0.00002168024,0.000120506,0.0001964072,0.0000492506],"domain_scores_gemma":[0.9995868,0.0001802535,0.00003352151,0.00007735728,0.00009892005,0.00002329633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001902314,0.00007030404,0.0006658821,0.0004213797,0.00008212691,0.0003390633,0.0003708988,0.2574919,0.178592,0.176691,0.005884305,0.3792008],"study_design_scores_gemma":[0.00001459285,0.00002077507,0.000233829,0.00001110663,0.00001141334,0.0001487174,0.00002460108,0.9058182,0.03983166,0.0418409,0.01202107,0.00002315302],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002321179,0.0001713315,0.9954205,0.00008098562,0.00001685902,0.00002516502,0.00004438403,0.0004521142,0.00146746],"genre_scores_gemma":[0.09890295,0.0005626005,0.8927283,0.00007701971,0.00003823549,0.0001410125,0.0002653684,0.0003822335,0.006902209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004266877,"threshold_uncertainty_score":0.01427418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02450951655609091,"score_gpt":0.2700753269616486,"score_spread":0.2455658104055577,"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."}}