{"id":"W2156040653","doi":"10.82308/37532","title":"Object detection and analysis using coherency filtering","year":2006,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Object (grammar); Computer vision; Artificial intelligence; Object detection; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0006965615,0.0006162669,0.0007436242,0.003132064,0.0004298907,0.001384913,0.0009142726,0.0006175063,0.001840796],"category_scores_gemma":[0.002401163,0.0004131566,0.0007208164,0.001795846,0.0005788432,0.001442929,0.0009228688,0.0005120409,0.0009333129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005055479,"about_ca_system_score_gemma":0.0006033582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004269161,"about_ca_topic_score_gemma":0.003947519,"domain_scores_codex":[0.9991726,0.00009768573,0.00003995319,0.000190596,0.0004320529,0.00006710679],"domain_scores_gemma":[0.9993016,0.0002061441,0.00009472751,0.0001450306,0.0002222979,0.00003026458],"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":[0.0001139933,0.00005565845,0.001697288,0.0001441244,0.00007962797,0.000140009,0.0002426471,0.03771044,0.188417,0.0111824,0.001519258,0.7586976],"study_design_scores_gemma":[0.00001762285,0.0001220205,0.00741752,0.00002556962,0.00006739243,0.0003603738,0.0001247918,0.8877717,0.08035011,0.01266167,0.01103113,0.00005011892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01408594,0.000230935,0.9837293,0.00004818336,0.00002005582,0.00003107565,0.00003823862,0.0004990827,0.001317233],"genre_scores_gemma":[0.2894297,0.0008971785,0.7043201,0.00009504871,0.0001207257,0.0001117252,0.0003596613,0.0002516565,0.004414116],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004269161,"threshold_uncertainty_score":0.008488595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01802396364940164,"score_gpt":0.2701737063199789,"score_spread":0.2521497426705773,"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."}}