{"id":"W7106855354","doi":"10.48448/dgpw-sq85","title":"Building Resource-Constrained Language Agents: A Korean Case Study on Chemical Toxicity Information","year":2025,"lang":"","type":"other","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Key (lock); Software deployment; Baseline (sea); Language model; Work (physics); Security token","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":[0.002014826,0.0006266222,0.0003214746,0.0002745282,0.000885529,0.00108977,0.001402096,0.001229059,0.003700106],"category_scores_gemma":[0.00429986,0.0002832613,0.0003897142,0.0003787897,0.0009174201,0.00286743,0.00163435,0.001052579,0.001131912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029524,"about_ca_system_score_gemma":0.001472413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008354886,"about_ca_topic_score_gemma":0.01328925,"domain_scores_codex":[0.9987962,0.000778308,0.00007024078,0.0001418656,0.000129423,0.00008391333],"domain_scores_gemma":[0.9973636,0.001711647,0.0001590519,0.0002977901,0.0002662666,0.0002015256],"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":[0.002802325,0.002887893,0.02809086,0.002941097,0.0002618573,0.0168929,0.03009461,0.3262579,0.1050455,0.08979689,0.04176299,0.3531651],"study_design_scores_gemma":[0.0003802019,0.0008885232,0.003104602,0.0001397854,0.0001746934,0.001876455,0.01022338,0.7594871,0.07034617,0.01905324,0.1341482,0.000177669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7264462,0.0005714244,0.238186,0.002847627,0.0001194658,0.0009427967,0.00129379,0.004072348,0.02552028],"genre_scores_gemma":[0.8161855,0.0002467458,0.1688124,0.0004804503,0.00001325833,0.0002340928,0.001124826,0.0004008717,0.01250184],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008354886,"threshold_uncertainty_score":0.01661247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246778519576444,"score_gpt":0.3449809500510792,"score_spread":0.3125131648553148,"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."}}