{"id":"W1499038423","doi":"10.1007/11866565_99","title":"Spinal Crawlers: Deformable Organisms for Spinal Cord Segmentation and Analysis","year":2006,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Segmentation; Computer science; Spinal cord; Artificial intelligence; Computer vision; Polygon mesh; Magnetic resonance imaging; Image segmentation; Anatomy; Pattern recognition (psychology); Medicine; Neuroscience; Biology; Radiology","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":[0.0004000556,0.00113126,0.0007760385,0.001044937,0.0004963159,0.0009923148,0.001714202,0.002150406,0.004789915],"category_scores_gemma":[0.001069559,0.0009581265,0.001193694,0.0007807591,0.0005245381,0.0007131987,0.001448902,0.001537823,0.002324281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005321887,"about_ca_system_score_gemma":0.0006032095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005095451,"about_ca_topic_score_gemma":0.01030357,"domain_scores_codex":[0.9998265,0.00002589342,0.000008983791,0.00005638109,0.00006419829,0.00001812128],"domain_scores_gemma":[0.9997577,0.0001124058,0.00002779347,0.00004296862,0.00003323798,0.00002587088],"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":[0.0002480448,0.00007811973,0.001418746,0.0004651249,0.0002138219,0.0003625016,0.0002753168,0.377082,0.05608667,0.01565843,0.02687909,0.5212321],"study_design_scores_gemma":[0.00002039776,0.00002389024,0.0003721303,0.00002155584,0.00001722421,0.0000956899,0.000020904,0.9783264,0.007334935,0.006226435,0.007523361,0.00001700517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008457367,0.0004043451,0.9773235,0.0001808943,0.000109129,0.0001010249,0.0007227645,0.01164506,0.001055911],"genre_scores_gemma":[0.08342344,0.0005401203,0.9064023,0.0001806132,0.00004558772,0.000264448,0.001695869,0.001808858,0.005638773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005095451,"threshold_uncertainty_score":0.01602387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.016860543094133,"score_gpt":0.2951380919553125,"score_spread":0.2782775488611795,"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."}}