{"id":"W2006461528","doi":"10.1145/2451236.2451238","title":"A gradient-based implicit blend","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"European Research Council; Natural Sciences and Engineering Research Council of Canada; Networks of Centres of Excellence of Canada; Agence Nationale de la Recherche; Intel Corporation","keywords":"Constructive; Merge (version control); Computer science; Composition (language); Animation; Binary number; Polygon mesh; Theoretical computer science; Topology (electrical circuits); Algorithm; Computational science; Computer graphics (images); Parallel computing; Mathematics; Programming language; Process (computing); Arithmetic","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":[],"consensus_categories":[],"category_scores_codex":[0.00004508493,0.0001431188,0.0001300794,0.0002933545,0.0001255093,0.000040716,0.000188372,0.00008138636,0.0002476497],"category_scores_gemma":[0.000004756791,0.0001396315,0.0001819262,0.0004841179,0.00002666653,0.00008493484,9.090652e-7,0.0002399736,0.00017331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002030341,"about_ca_system_score_gemma":0.00000703341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008964833,"about_ca_topic_score_gemma":0.00005970172,"domain_scores_codex":[0.9993148,0.00001139983,0.0001591328,0.0001542528,0.0001340983,0.0002263597],"domain_scores_gemma":[0.9993227,0.00006029238,0.00001168361,0.0004660607,0.00004322973,0.00009603098],"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":[0.000004381402,0.0001460635,0.0001463588,0.00005755054,0.0002563531,0.000002744452,0.000130035,0.9429145,0.002470017,0.0001921528,0.001043834,0.05263604],"study_design_scores_gemma":[0.0004060871,0.00006089171,0.0005354101,0.00003527273,0.0001372229,0.000002970183,0.00006332096,0.9887284,0.004434282,0.004394149,0.0008329268,0.0003690537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1745979,0.00008824543,0.8234949,0.0006212232,0.000154876,0.0001036791,0.00001956327,0.0005351644,0.0003844382],"genre_scores_gemma":[0.9973255,0.00009736853,0.002122433,0.0002596846,0.0000174227,0.00006690189,0.00000744022,0.00003214622,0.000071075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8227276,"threshold_uncertainty_score":0.5694008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01292285606899561,"score_gpt":0.2106140240587892,"score_spread":0.1976911679897936,"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."}}