{"id":"W3208805586","doi":"10.1109/iccvw54120.2021.00236","title":"Evaluation of Latent Space Learning with Procedurally-Generated Datasets of Shapes","year":2021,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Set (abstract data type); Artificial neural network; Artificial intelligence; Contrast (vision); Space (punctuation); Machine learning; Pattern recognition (psychology); Latent semantic analysis; Data mining","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":[0.01145959,0.002314999,0.001164645,0.002036084,0.0007656161,0.002544966,0.002804783,0.002612356,0.001899514],"category_scores_gemma":[0.03689723,0.0005146107,0.001787899,0.001664465,0.002003523,0.003438406,0.0025976,0.002348668,0.0006658498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001966004,"about_ca_system_score_gemma":0.001319574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007713423,"about_ca_topic_score_gemma":0.0100265,"domain_scores_codex":[0.9948966,0.002478166,0.0003723578,0.001107674,0.0009256547,0.000219414],"domain_scores_gemma":[0.9791926,0.0132119,0.001185097,0.00391471,0.001884729,0.0006109829],"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":[0.0007619605,0.0004657102,0.008546461,0.0004853844,0.0004201099,0.0000851213,0.0001528673,0.9174154,0.003107226,0.004929767,0.003247659,0.06038238],"study_design_scores_gemma":[0.00004996669,0.0002560158,0.001426302,0.00005408121,0.00002678718,0.0000558264,0.00007456227,0.9908146,0.002875874,0.003534401,0.0008079083,0.00002366532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5475854,0.003040209,0.4272105,0.001686398,0.0003912522,0.0006760262,0.007515271,0.005353246,0.006541674],"genre_scores_gemma":[0.8123017,0.0007483269,0.1637145,0.0004625352,0.0001212782,0.0004570277,0.02007638,0.0006028196,0.001515404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01145959,"threshold_uncertainty_score":0.06060481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02567124364967769,"score_gpt":0.2449768030833032,"score_spread":0.2193055594336255,"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."}}