{"id":"W2085435911","doi":"10.1109/isspa.2012.6310475","title":"Shape recognition on a Riemannian manifold","year":2012,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Shape analysis (program analysis); Riemannian manifold; Manifold (fluid mechanics); Active shape model; Robustness (evolution); Artificial intelligence; Heat kernel signature; Topological skeleton; Invariant (physics); Pattern recognition (psychology); Topology (electrical circuits); Computer science; Mathematical analysis; Segmentation; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005769982,0.0007198348,0.00121372,0.001270794,0.000465286,0.001437344,0.001432947,0.001136467,0.003519592],"category_scores_gemma":[0.002646299,0.0003435598,0.001346709,0.001071815,0.001055093,0.002506215,0.001650593,0.001031188,0.002790517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007036274,"about_ca_system_score_gemma":0.0005415931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002339034,"about_ca_topic_score_gemma":0.001353721,"domain_scores_codex":[0.9989779,0.0001939173,0.00006833948,0.0003114741,0.0003643912,0.0000839494],"domain_scores_gemma":[0.9990653,0.0001624373,0.00008871999,0.0003943007,0.0002341693,0.00005508298],"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":[0.0001333383,0.00008600521,0.00197235,0.0002134673,0.0001086165,0.0002769935,0.0002484074,0.192801,0.07709719,0.08747078,0.006139867,0.633452],"study_design_scores_gemma":[0.000006527285,0.000108444,0.001037525,0.00001357795,0.00001150997,0.000215753,0.00005561649,0.9396537,0.01695385,0.03506825,0.006843082,0.00003225798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02018424,0.0001783302,0.975733,0.0001546137,0.0000478451,0.00005082032,0.00008421327,0.001683156,0.00188371],"genre_scores_gemma":[0.3737207,0.0003898146,0.6191679,0.0002427454,0.0001181374,0.0001108884,0.0007607622,0.0005371444,0.00495189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003519592,"threshold_uncertainty_score":0.01177424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04917652892068731,"score_gpt":0.2676995970085601,"score_spread":0.2185230680878728,"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."}}