{"id":"W2268351550","doi":"10.1109/ccece.2014.6901162","title":"Notice of Violation of IEEE Publication Principles: Hand gesture recognition framework for recognizing sign gestures and handling movement epenthesis using Level Building nested dynamic programming approach","year":2014,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gesture; Computer science; Notice; Sign (mathematics); Sign language; Movement (music); Sentence; Gesture recognition; Feature (linguistics); Permission; Speech recognition; Artificial intelligence; Linguistics; Law; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":{"nature":"Retraction","reason":"Concerns/Issues about Referencing/Attributions;Date of Article and/or Notice Unknown;Euphemisms for Plagiarism;Investigation by Journal/Publisher;Plagiarism of Text;","date":"9/18/2014 0:00","openalex_flagged":false},"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.02489046,0.00118563,0.00168369,0.001962133,0.003668333,0.01467877,0.00418687,0.009677202,0.02892029],"category_scores_gemma":[0.06761955,0.00122487,0.001545555,0.001849734,0.003736389,0.005285178,0.004614754,0.01409349,0.0230904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004382728,"about_ca_system_score_gemma":0.01042554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007526193,"about_ca_topic_score_gemma":0.00508056,"domain_scores_codex":[0.9656046,0.004701183,0.004299519,0.002321404,0.02101387,0.002059405],"domain_scores_gemma":[0.9409003,0.01369377,0.00286998,0.008560032,0.03172127,0.002254664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003862298,0.0001909358,0.001194672,0.0004583864,0.0001231717,0.001290587,0.0007969326,0.003930239,0.01120399,0.1217418,0.6743151,0.184368],"study_design_scores_gemma":[0.00007899915,0.0002150065,0.0009048297,0.000287564,0.0000568246,0.0009786626,0.0001780399,0.01743318,0.0106394,0.02897988,0.9401194,0.0001281505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.009418164,0.005045139,0.5758665,0.1243007,0.08988982,0.001383046,0.002174106,0.01096307,0.1809595],"genre_scores_gemma":[0.1550416,0.008241062,0.2639021,0.04998575,0.03158272,0.002530126,0.007461272,0.005822465,0.475433],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9903228,"threshold_uncertainty_score":0.131635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09629791187075125,"score_gpt":0.2986114663468265,"score_spread":0.2023135544760752,"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."}}