{"id":"W2914399902","doi":"10.1109/tvcg.2019.2896895","title":"Micrography QR Codes","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Ministry of Science and Technology, Taiwan","keywords":"Micrography; Computer science; Decoding methods; Artificial intelligence; Computer vision; Embedding; Algorithm; Optics","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":[],"consensus_categories":[],"category_scores_codex":[0.0005255796,0.0009996712,0.0005824951,0.001044217,0.0005332863,0.001313452,0.0009876075,0.00086531,0.01668215],"category_scores_gemma":[0.004298267,0.0004270285,0.0007283977,0.0006606609,0.0008549613,0.001282705,0.001425436,0.001032395,0.00818985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004808891,"about_ca_system_score_gemma":0.0007584965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001100112,"about_ca_topic_score_gemma":0.001369382,"domain_scores_codex":[0.9993019,0.00008572199,0.0000503773,0.000170754,0.0003348712,0.00005634549],"domain_scores_gemma":[0.9984823,0.0004191649,0.0001803468,0.0003667507,0.0004747014,0.00007674428],"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":[0.0004196189,0.00006545166,0.00102292,0.0005731792,0.00004590695,0.00047978,0.000527976,0.03653575,0.1091047,0.06400382,0.02249049,0.7647305],"study_design_scores_gemma":[0.0001181124,0.0004997086,0.001084497,0.0001641527,0.000040876,0.001867935,0.0002638266,0.5776445,0.2163863,0.03778306,0.1640083,0.0001388888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006532932,0.0002087777,0.9826932,0.0001735081,0.0001708444,0.0001620511,0.0002358388,0.004675247,0.005147716],"genre_scores_gemma":[0.08560098,0.0003509332,0.8990439,0.0002358775,0.00007316691,0.0001915417,0.000630415,0.001254705,0.01261851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01668215,"threshold_uncertainty_score":0.05580735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226558974203053,"score_gpt":0.2499978649221933,"score_spread":0.2377322751801628,"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."}}