{"id":"W7160196152","doi":"10.1109/iccv51701.2025.01727","title":"PASTA: Part-Aware Sketch-to-3D Shape Generation with Text-Aligned Prior","year":2025,"lang":"","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"National Research Foundation of Korea; National Science Foundation","keywords":"Noise (video); Set (abstract data type); Process (computing); Identification (biology)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002880026,0.0005596453,0.0006206376,0.0004548776,0.0003816154,0.0003452986,0.0002999495,0.0002513639,0.001966563],"category_scores_gemma":[0.00003883017,0.0004940865,0.0001973655,0.001381891,0.00003753236,0.0002180838,0.0001024949,0.0002167176,0.0003725307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001773282,"about_ca_system_score_gemma":0.0001733208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001143092,"about_ca_topic_score_gemma":0.0005243204,"domain_scores_codex":[0.9972972,0.00006826623,0.0007328102,0.0008153815,0.0003991596,0.0006871762],"domain_scores_gemma":[0.9986449,0.00005741296,0.00006804457,0.0006947881,0.000270593,0.0002642848],"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":[0.00004375096,0.0001257412,0.0005600832,0.0002197511,0.0008891162,0.00002268654,0.0005292092,0.8606936,0.002528101,0.0005180381,0.009509156,0.1243608],"study_design_scores_gemma":[0.0006094226,0.0001039762,0.0001354992,0.0003118648,0.0005226601,0.000002573044,0.0002820671,0.9888593,0.00325163,0.00002573427,0.005280627,0.0006146262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1115669,0.0008267372,0.8713781,0.002314562,0.0005749051,0.0004716683,0.00003078236,0.0005022805,0.01233407],"genre_scores_gemma":[0.9733509,0.0002071534,0.007546188,0.000782614,0.0004994543,0.0000716393,0.00005971295,0.00007459722,0.01740775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8638319,"threshold_uncertainty_score":0.9997511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382730558601386,"score_gpt":0.2304427842276669,"score_spread":0.2166154786416531,"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."}}