{"id":"W2041306713","doi":"10.1007/s11263-009-0279-0","title":"Contextual Part Analogies in 3D Objects","year":2009,"lang":"en","type":"article","venue":"International Journal of Computer Vision","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":169,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Matching (statistics); Object (grammar); Hierarchy; Artificial intelligence; Context (archaeology); Similarity (geometry); Graph; Pattern recognition (psychology); Scene graph; Function (biology); Simple (philosophy); Shape analysis (program analysis); Information retrieval; Theoretical computer science; Image (mathematics); Mathematics","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":[0.0006820939,0.0004680411,0.0008423947,0.001684024,0.0008536478,0.002222439,0.001745694,0.001635835,0.0113489],"category_scores_gemma":[0.007022175,0.0007360325,0.0008135085,0.001952498,0.001545268,0.004736383,0.002344182,0.00132774,0.0005982934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007593152,"about_ca_system_score_gemma":0.0003688656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002545139,"about_ca_topic_score_gemma":0.002812863,"domain_scores_codex":[0.9990382,0.000163774,0.00003964216,0.0003323049,0.0003469868,0.00007902996],"domain_scores_gemma":[0.9979293,0.0007250568,0.0002093311,0.0007511856,0.0002634329,0.0001216953],"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":[0.001492322,0.0002698483,0.005153761,0.000513325,0.0001832424,0.001655578,0.001239406,0.2060464,0.04802973,0.3187903,0.004016757,0.4126093],"study_design_scores_gemma":[0.00005634531,0.0001981398,0.006750457,0.00006439927,0.00007657761,0.0008813958,0.000399941,0.7100052,0.007582572,0.2668487,0.007056794,0.00007955654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2915813,0.00149382,0.6850327,0.0004630485,0.0003099785,0.0001122662,0.0003914308,0.001329978,0.01928549],"genre_scores_gemma":[0.9545326,0.0003776138,0.0423777,0.0001258758,0.00005993831,0.00003165481,0.000215282,0.0001919693,0.00208734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0113489,"threshold_uncertainty_score":0.03796583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009702834041186693,"score_gpt":0.2614141826444403,"score_spread":0.2517113486032536,"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."}}