{"id":"W2268663799","doi":"10.1080/21681163.2015.1077164","title":"Constructing average models of quasi-spherical objects: application to corneal topographies","year":2015,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital Maisonneuve-Rosemont; Université de Montréal; Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Cornea; Computer vision; Surface (topology); Artificial intelligence; Matching (statistics); Image registration; Computed tomography; Algorithm; Biomedical engineering; Mathematics; Optics; Geometry; Image (mathematics); Physics; Medicine; Surgery","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":[0.0009645366,0.0006128965,0.0007174904,0.001171982,0.0004607064,0.001894176,0.001097864,0.001213197,0.001424056],"category_scores_gemma":[0.003556955,0.0006865207,0.001338464,0.0009954998,0.0008235807,0.0008938049,0.001517475,0.0008481918,0.0004564675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005855717,"about_ca_system_score_gemma":0.0007419091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005227951,"about_ca_topic_score_gemma":0.004981438,"domain_scores_codex":[0.9995537,0.0001169574,0.00002647881,0.00005862778,0.000206637,0.00003756105],"domain_scores_gemma":[0.9987828,0.0006657547,0.0001081723,0.000240975,0.0001420884,0.00006024047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009323506,0.00003392046,0.001320501,0.0001069353,0.00006648667,0.0002548689,0.0005013886,0.8330578,0.02734802,0.01729546,0.0007059394,0.1192155],"study_design_scores_gemma":[0.000002340785,0.00001321338,0.0001771802,0.000003142262,0.000004790952,0.00008806798,0.00002624483,0.9936373,0.002325123,0.003008385,0.0007025866,0.000011698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02701126,0.00008161755,0.9713637,0.00005613741,0.00001068316,0.00003342819,0.00004949014,0.0007364764,0.0006573285],"genre_scores_gemma":[0.4076114,0.0003189301,0.5901008,0.00003178937,0.000023475,0.00006070005,0.0001935479,0.0005397752,0.001119537],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005227951,"threshold_uncertainty_score":0.01039505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949564817604608,"score_gpt":0.3048845000762574,"score_spread":0.2853888519002113,"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."}}