{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"4af2eeba026a","filters":{"venue":"Indian Conference on Computer Vision, Graphics and Image Processing"}},"results":[{"id":"W45057407","doi":"","title":"Low-Band-Shifted Hierarchical Backward Motion Estimation, Compensation for Wavelet-Based Video Coding.","year":2002,"lang":"en","type":"article","venue":"Indian Conference on Computer Vision, Graphics and Image Processing","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Motion compensation; Motion estimation; Quarter-pixel motion; Computer science; Wavelet; Inter frame; Reference frame; Artificial intelligence; Computer vision; Wavelet transform; Block-matching algorithm; Quantization (signal processing); Algorithm; Mathematics; Frame (networking); Video processing; Telecommunications; Video tracking","authors":[{"name":"Yufei Yuan","is_ca":true},{"name":"Mrinal Mandal","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0267959281425011,"gpt":0.2867228533230879,"spread":0.2599269251805869,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028613,0.000369026,0.0002477482,0.0003626126,0.0002065481,0.0002646115,0.000540736,0.0003713251,0.0009582284],"category_scores_gemma":[0.000452968,0.0001540852,0.0002411672,0.0004170639,0.0002202002,0.0004103541,0.0003203648,0.0004874694,0.0005306549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002922587,"about_ca_system_score_gemma":0.000462829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002289441,"about_ca_topic_score_gemma":0.005013011,"domain_scores_codex":[0.9998599,0.00002708186,0.000008027141,0.00001485379,0.00007796739,0.0000121982],"domain_scores_gemma":[0.9998947,0.00002058006,0.0000174719,0.0000231417,0.00003533706,0.000008783431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001990364,0.00008291905,0.0005413105,0.0002331156,0.00004462563,0.0001927571,0.00009787066,0.04212206,0.3909527,0.03462446,0.006476786,0.5244324],"study_design_scores_gemma":[0.00003759025,0.0001655709,0.0007857367,0.00003511611,0.00003407097,0.0003620555,0.00001987119,0.8937879,0.08486802,0.005444972,0.01442879,0.00003020848],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009345107,0.0009497233,0.988112,0.0000688026,0.00006085896,0.00005494564,0.00005230579,0.0003317653,0.001024468],"genre_scores_gemma":[0.1688527,0.001147316,0.8250591,0.00009755915,0.00006093764,0.00009826123,0.0003990813,0.00004841334,0.004236667],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002289441,"threshold_uncertainty_score":0.004552186,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W34256809","doi":"10.1186/s13059-021-02408-w","title":"Encoding Quadrilateral Meshes in 2.40 bits per Vertex.","year":2004,"lang":"en","type":"article","venue":"Indian Conference on Computer Vision, Graphics and Image Processing","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor; University of Toronto","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Vertex (graph theory); Polygon mesh; Quadrilateral; Encoding (memory); Coding (social sciences); Computer science; Combinatorics; Mathematics; Algorithm; Discrete mathematics; Arithmetic; Artificial intelligence; Physics; Computer graphics (images); Statistics","authors":[{"name":"Pawel Kosicki","is_ca":true},{"name":"Asish Mukhopadhyay","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01784777943989866,"gpt":0.2720468687869445,"spread":0.2541990893470458,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002706706,0.0008027087,0.0005476006,0.0007734292,0.0003857333,0.001291148,0.00107602,0.000916102,0.04411066],"category_scores_gemma":[0.002986821,0.0003656543,0.0006487559,0.001535789,0.000351698,0.001771281,0.00135968,0.0007859272,0.009091229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005301155,"about_ca_system_score_gemma":0.0004335627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002574033,"about_ca_topic_score_gemma":0.006209296,"domain_scores_codex":[0.9996419,0.00006872999,0.00003808074,0.00004886521,0.0001398372,0.00006254714],"domain_scores_gemma":[0.9992674,0.0002730629,0.00003911586,0.0001997771,0.0001915046,0.00002914158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001291266,0.0001465015,0.001221426,0.0008984073,0.00008570035,0.0004172793,0.0003576198,0.05958882,0.02315705,0.06287753,0.1219044,0.728054],"study_design_scores_gemma":[0.0003044151,0.000326205,0.0008381477,0.0003494401,0.00007119405,0.000534179,0.0005420289,0.4698013,0.05083878,0.1632803,0.3130172,0.00009673013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03351508,0.002072875,0.8522221,0.001346782,0.001156091,0.0003311029,0.01350374,0.03014008,0.06571213],"genre_scores_gemma":[0.3783533,0.001149235,0.5640706,0.0006602647,0.0001266542,0.0005379632,0.01872694,0.002630671,0.03374438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04411066,"threshold_uncertainty_score":0.1475648,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}