{"id":"W4286611260","doi":"10.1145/3528223.3530106","title":"Sketch2Pose","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Bitmap; Computer science; Character (mathematics); Sketch; Code (set theory); Key (lock); Artificial intelligence; Process (computing); Computer graphics (images); Software; Computer vision; Programming language; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006536848,0.00006426608,0.00004929326,0.0001678356,0.0002777166,0.00001318995,0.0001283511,0.00002094283,0.001428944],"category_scores_gemma":[0.000002387613,0.00007668353,0.00006152507,0.000295611,0.00001216259,0.00005711976,0.000001833134,0.0002666555,0.00005447037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003313141,"about_ca_system_score_gemma":0.000004868972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000186815,"about_ca_topic_score_gemma":0.000008697514,"domain_scores_codex":[0.9995784,0.0000196704,0.00009036162,0.00007643212,0.0001398092,0.00009533083],"domain_scores_gemma":[0.9997128,0.0000234079,0.000007540888,0.0002124398,0.000009374223,0.00003442209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004257854,0.0006678876,0.0001652314,0.0001085322,0.0002239309,0.00002211764,0.003120197,0.7752152,0.007424784,0.02463204,0.01151222,0.1768653],"study_design_scores_gemma":[0.002860408,0.0008508291,0.01154483,0.00003834311,0.0001553455,0.0001034393,0.002017052,0.186086,0.009416196,0.04826365,0.7369488,0.001715056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3885292,0.0001703659,0.594909,0.001711654,0.002102852,0.0003790673,0.0001458867,0.002514409,0.0095376],"genre_scores_gemma":[0.9989883,0.00005381412,0.0003683864,0.0002769435,0.00001442965,0.00004522965,0.000009084848,0.00001843747,0.0002253142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7254366,"threshold_uncertainty_score":0.9994839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699147310995826,"score_gpt":0.2159524684977188,"score_spread":0.1989609953877605,"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."}}