{"id":"W2141441007","doi":"10.1109/tbme.2008.923106","title":"A Novel 3-D Image-Based Morphological Method for Phenotypic Analysis","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Morphometrics; Shape analysis (program analysis); Landmark; Artificial intelligence; Image registration; Pattern recognition (psychology); Image processing; Orientation (vector space); Scale (ratio); Computer vision; Computer science; Image (mathematics); Voxel; Mathematics; Biology; Geometry; Cartography; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003461695,0.0002223876,0.0004246905,0.0004861399,0.0001828541,0.00001615885,0.0001843855,0.0002279447,0.0004374872],"category_scores_gemma":[0.0001370255,0.0001789577,0.0004601105,0.001266901,0.00007779897,0.00004901237,0.000001498823,0.0003038137,0.00001574968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006583297,"about_ca_system_score_gemma":0.00003539834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001127605,"about_ca_topic_score_gemma":0.000001105127,"domain_scores_codex":[0.9985566,0.00002785684,0.0003951174,0.0003673942,0.0003034433,0.0003495538],"domain_scores_gemma":[0.9981157,0.001249407,0.00005994501,0.0002921497,0.00006362334,0.000219239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004608962,0.01145096,0.00003218115,0.0004742292,0.004518009,0.0002970317,0.0002908799,0.2795777,0.6608981,0.01542641,0.003897922,0.02267575],"study_design_scores_gemma":[0.002050987,0.0003245216,0.0004403896,0.00002495973,0.00082287,0.0000725542,0.0000126285,0.9785041,0.01531392,0.0003312021,0.001618887,0.0004829325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005618378,0.00000696275,0.9930793,0.0003443742,0.0002184614,0.0002541191,0.0001502612,0.0002934436,0.00003470967],"genre_scores_gemma":[0.3696392,0.00000324312,0.6299528,0.0001162381,0.00005382758,0.0001263,0.00001340057,0.00002012235,0.0000748037],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6989265,"threshold_uncertainty_score":0.7297683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04536351878749747,"score_gpt":0.3007374252170686,"score_spread":0.2553739064295711,"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."}}