{"id":"W4385595405","doi":"10.1145/3573128.3604901","title":"WEATHERGOV+","year":2023,"lang":"en","type":"article","venue":"","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Automatic summarization; Computer science; Pipeline (software); Table (database); Information retrieval; Segmentation; Row; Information extraction; Artificial intelligence; Data mining; Natural language processing; Database","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":[0.0006581108,0.002101543,0.0009517505,0.002346511,0.0008759195,0.002356449,0.002463923,0.00153925,0.1091692],"category_scores_gemma":[0.003216321,0.0006494942,0.001131437,0.003360283,0.0003915377,0.003675871,0.003036361,0.001359136,0.1445821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008195337,"about_ca_system_score_gemma":0.0009650643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132397,"about_ca_topic_score_gemma":0.02427411,"domain_scores_codex":[0.9989733,0.0001233773,0.00008953131,0.000337848,0.0003337754,0.0001421396],"domain_scores_gemma":[0.9985572,0.0001977967,0.000133935,0.0005465067,0.0003973885,0.0001672699],"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":[0.0002479785,0.00005624459,0.001134783,0.0008020492,0.00002896132,0.00007044621,0.0001078386,0.0005940964,0.001441965,0.001787027,0.9625726,0.03115606],"study_design_scores_gemma":[0.000101116,0.00005667831,0.003097296,0.00009397831,0.00001426749,0.0001554532,0.0001473789,0.00169653,0.002334871,0.002416854,0.9898468,0.00003878395],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004198528,0.0006448321,0.003639761,0.000373864,0.0004100325,0.0002042976,0.9321513,0.03188407,0.02649335],"genre_scores_gemma":[0.004399943,0.0001858021,0.0053066,0.0001584174,0.00004301641,0.0001512959,0.9792392,0.002524721,0.007990997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1091692,"threshold_uncertainty_score":0.3652075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02109561427660894,"score_gpt":0.2653373836700727,"score_spread":0.2442417693934638,"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."}}