{"id":"W7083435586","doi":"10.5281/zenodo.17211041","title":"Using AI in Writing-Intensive Disciplines: Understanding LLM strengths and weaknesses","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Ginger and Zingiberaceae research","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Strengths and weaknesses; Presentation (obstetrics); Generative grammar; Rubric; Proofreading; CLARITY; Creativity","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":[0.006864623,0.0005990047,0.0003163778,0.001220045,0.001589082,0.006817053,0.00108708,0.001353414,0.009895288],"category_scores_gemma":[0.01699306,0.000235226,0.0002633074,0.0007035814,0.004426276,0.006390773,0.00378988,0.002344216,0.003246332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002164909,"about_ca_system_score_gemma":0.002039314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005335919,"about_ca_topic_score_gemma":0.000968363,"domain_scores_codex":[0.9972976,0.001369513,0.0001873553,0.0002968268,0.000649164,0.0001996074],"domain_scores_gemma":[0.9893754,0.006793816,0.0007452727,0.0007683347,0.001425196,0.0008919283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001956793,0.0002310762,0.004122747,0.001454598,0.00001796234,0.001185516,0.0851088,0.001379375,0.01801546,0.2611249,0.07244437,0.5547195],"study_design_scores_gemma":[0.00002278015,0.0001671474,0.003349651,0.001447812,0.00001452626,0.001287477,0.02828121,0.004758321,0.0132832,0.1556855,0.7916386,0.00006368423],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1518144,0.009869594,0.317509,0.09457859,0.003767742,0.0005410569,0.0003620103,0.004162952,0.4173948],"genre_scores_gemma":[0.6243732,0.006800484,0.2277824,0.009473492,0.001125817,0.0006108822,0.0003078824,0.001843262,0.1276827],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.009895288,"threshold_uncertainty_score":0.036304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2002931209324913,"score_gpt":0.4534354723438778,"score_spread":0.2531423514113865,"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."}}