{"id":"W49896968","doi":"","title":"Application of neural networks to the segmentation of microscopy images","year":2004,"lang":"en","type":"book","venue":"Nova Science Publishers, Inc. eBooks","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Segmentation; Artificial intelligence; Computer science; Computer vision; Artificial neural network; Feature (linguistics); Pattern recognition (psychology); Image segmentation; Projection (relational algebra); Relation (database); Data mining; Algorithm","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":[0.0003366425,0.0005680467,0.0003746477,0.0006591917,0.0001902447,0.0006782939,0.0005213125,0.0005762475,0.002007438],"category_scores_gemma":[0.0009427309,0.0003440746,0.0003572154,0.0009015675,0.0003574866,0.0005347122,0.0003606745,0.0006179729,0.0008140249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006658597,"about_ca_system_score_gemma":0.0002439828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002619742,"about_ca_topic_score_gemma":0.002754638,"domain_scores_codex":[0.9998338,0.00003288284,0.00001005153,0.00003494969,0.00007528177,0.00001303438],"domain_scores_gemma":[0.999697,0.0001648165,0.00001456807,0.0000232794,0.00009209559,0.000008281705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009936118,0.00003300371,0.0003030696,0.0002907223,0.00005624357,0.0001793969,0.00008013286,0.1635976,0.04001467,0.008644018,0.00645636,0.7802454],"study_design_scores_gemma":[0.000006562217,0.00003811288,0.0005176355,0.00003691083,0.00001424748,0.0001457334,0.00001992098,0.955931,0.02073283,0.007807179,0.01473425,0.00001565741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01268958,0.004469076,0.9704898,0.0003603118,0.0002070747,0.0000576168,0.00009273777,0.001847438,0.009786359],"genre_scores_gemma":[0.1082673,0.006196224,0.8665117,0.0001632103,0.0001357335,0.0001262671,0.0002780307,0.0002462492,0.01807529],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002619742,"threshold_uncertainty_score":0.006715477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008400917725411381,"score_gpt":0.2798887621688787,"score_spread":0.2714878444434673,"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."}}