{"id":"W4402933071","doi":"10.1002/gdj3.261","title":"Automation of historical weather data rescue","year":2024,"lang":"en","type":"article","venue":"Geoscience Data Journal","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Environment and Climate Change Canada","keywords":"Automation; Computer science; Aeronautics; Systems engineering; Data science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001100749,0.0007102513,0.0006077755,0.001667902,0.001165212,0.001631971,0.001091302,0.0007217189,0.006288681],"category_scores_gemma":[0.005056958,0.0003961501,0.0006701899,0.001122807,0.0005591642,0.0007525123,0.001369711,0.0009276793,0.006690629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006066146,"about_ca_system_score_gemma":0.0014097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006069751,"about_ca_topic_score_gemma":0.00599971,"domain_scores_codex":[0.9986959,0.0002017478,0.0001401367,0.0004675715,0.0004095953,0.00008511477],"domain_scores_gemma":[0.9952801,0.001241157,0.0003179097,0.001460485,0.001514337,0.0001861085],"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":[0.0003999685,0.000184373,0.004446248,0.0005857889,0.00004396652,0.001235915,0.002668985,0.01879679,0.1142929,0.002323391,0.0414243,0.8135973],"study_design_scores_gemma":[0.0001507425,0.000246847,0.01905545,0.0002779579,0.0000729199,0.001216854,0.003279521,0.2698831,0.4181365,0.01013432,0.2773163,0.0002295261],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08183619,0.0004278592,0.7892697,0.001036675,0.0003788819,0.0007934295,0.006607922,0.1030601,0.01658933],"genre_scores_gemma":[0.2802907,0.0003308182,0.6871197,0.0003581693,0.00009929611,0.0003608698,0.01348397,0.003494678,0.01446183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006288681,"threshold_uncertainty_score":0.0210377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0765346719700735,"score_gpt":0.3237836979278009,"score_spread":0.2472490259577274,"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."}}