{"id":"W3019597059","doi":"10.3934/mbe.2020182","title":"Robust table recognition for printed document images","year":2020,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Robustness (evolution); Table (database); Preprocessor; Pattern recognition (psychology); Distortion (music); Computer vision; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003799903,0.0001545351,0.0001941439,0.00008757657,0.00008553614,0.000324081,0.0006619074,0.00005080743,0.00007546153],"category_scores_gemma":[0.0007553126,0.0001329328,0.00007053547,0.0005750993,0.00004417117,0.0006662027,0.0001702717,0.00009683658,0.0001030755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002427532,"about_ca_system_score_gemma":0.0000275846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001173939,"about_ca_topic_score_gemma":9.65106e-8,"domain_scores_codex":[0.9986654,0.00001304625,0.0002930296,0.0004065098,0.0002739218,0.0003480727],"domain_scores_gemma":[0.9992427,0.0002304358,0.00005919374,0.0001870295,0.00009229688,0.000188298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002501007,0.0004890276,0.00004518273,0.001995782,0.00009170393,0.00003831248,0.003322124,0.002177134,0.4265449,0.3319525,0.008268686,0.2250496],"study_design_scores_gemma":[0.0002068022,0.0002352375,0.00002117478,0.00018905,0.00001175756,0.00001712474,0.00005365221,0.4935857,0.4760077,0.02676396,0.002490119,0.0004177048],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00189066,0.00002349703,0.9939725,0.002089053,0.00009024368,0.0004249894,0.000008290995,0.0008460326,0.0006547337],"genre_scores_gemma":[0.1654531,0.000009044725,0.8338722,0.0003698693,0.00006625126,0.0001715462,0.000003290516,0.00001244125,0.00004220659],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4914086,"threshold_uncertainty_score":0.5420843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03806920380089288,"score_gpt":0.2412476912217859,"score_spread":0.203178487420893,"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."}}