{"id":"W4293863186","doi":"10.1109/siu55565.2022.9864983","title":"A Criticism on Popular Sketch Datasets","year":2022,"lang":"en","type":"article","venue":"2022 30th Signal Processing and Communications Applications Conference (SIU)","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Sketch; Computer science; Task (project management); Sketch recognition; Similarity (geometry); Quality (philosophy); Data science; Criticism; Human–computer interaction; Information retrieval; Artificial intelligence; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01643816,0.001682626,0.001528245,0.005526958,0.001840992,0.00682327,0.006247511,0.002743944,0.007488321],"category_scores_gemma":[0.1240173,0.0008635696,0.002549997,0.01065115,0.001600607,0.008368562,0.005889502,0.003988436,0.01182513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001966469,"about_ca_system_score_gemma":0.002574573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004755577,"about_ca_topic_score_gemma":0.00515082,"domain_scores_codex":[0.9717034,0.005891031,0.00377619,0.003840647,0.01410631,0.0006825255],"domain_scores_gemma":[0.925144,0.02625732,0.001891891,0.0263932,0.01916437,0.001149306],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0007144514,0.0003408566,0.0145863,0.004487105,0.0005102804,0.0001799042,0.0005756447,0.008588286,0.003283845,0.04478469,0.5800011,0.3419475],"study_design_scores_gemma":[0.00009424175,0.0002022009,0.01119302,0.00102682,0.00007290972,0.001291864,0.0007208714,0.01905021,0.004922376,0.02203898,0.9392648,0.0001217023],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05383182,0.03532714,0.4158679,0.03360723,0.01151746,0.003200366,0.3291412,0.04026772,0.07723927],"genre_scores_gemma":[0.1656231,0.01105683,0.3070191,0.009455373,0.001979258,0.004084177,0.4777903,0.004033973,0.01895776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9835618,"threshold_uncertainty_score":0.08693433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03650949128462089,"score_gpt":0.3091533562823338,"score_spread":0.2726438649977129,"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."}}