{"id":"W6989481664","doi":"","title":"An automated approach for segmenting regions containing invasive ductal breast carcinomas in whole digital slides","year":2015,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"AI in cancer detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grading (engineering); Detector; Local binary patterns; Histogram; Pattern recognition (psychology); Ductal carcinoma; Binary number; Breast tissue","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007924081,0.0007009836,0.0005502703,0.00290865,0.0005578548,0.001077624,0.001079676,0.0008389573,0.002886412],"category_scores_gemma":[0.001335125,0.0003733855,0.0007989655,0.001277975,0.0003159561,0.0006616047,0.0005434559,0.0004255788,0.001915067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005265099,"about_ca_system_score_gemma":0.0009494988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0044176,"about_ca_topic_score_gemma":0.008808664,"domain_scores_codex":[0.9992902,0.00007208312,0.00004220914,0.0002448582,0.0002692025,0.00008143004],"domain_scores_gemma":[0.9993217,0.0001738794,0.00005757697,0.0001119725,0.0003004839,0.00003448494],"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":[0.0001668451,0.0001696802,0.002835525,0.0001411336,0.0000692887,0.0001338112,0.0001263938,0.006138382,0.1168619,0.001066802,0.005221813,0.8670685],"study_design_scores_gemma":[0.00008801098,0.0006667514,0.0408504,0.0001009374,0.0002664522,0.002254524,0.0004392063,0.6779347,0.2375803,0.004215528,0.03547546,0.0001277222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08053375,0.0005807655,0.9080268,0.0002155316,0.0001339819,0.0004494477,0.000842448,0.005995108,0.003222253],"genre_scores_gemma":[0.1337265,0.0004039552,0.8583218,0.00009785808,0.00005604253,0.0001913627,0.001517913,0.0001911788,0.005493334],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0044176,"threshold_uncertainty_score":0.009656012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02588411254503933,"score_gpt":0.2698799836445979,"score_spread":0.2439958710995585,"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."}}