{"id":"W7117536936","doi":"10.26434/chemrxiv-2025-dtt4k","title":"Gradient-Based Optimization of Force Field Parameters for Martini Lipid Models","year":2025,"lang":"","type":"article","venue":"ChemRxiv","topic":"Lipid Membrane Structure and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Force field (fiction); Heuristic; Workflow; Field (mathematics); Work (physics); Scale (ratio); Lipid bilayer; Observable","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":[0.001315403,0.001077496,0.0008695899,0.0006098848,0.000691501,0.0006163336,0.001941094,0.001338506,0.002876717],"category_scores_gemma":[0.003654786,0.0005262643,0.0007295676,0.0005572546,0.0007021493,0.0007584654,0.0009923673,0.001653886,0.0009254709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001365216,"about_ca_system_score_gemma":0.00243879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008591608,"about_ca_topic_score_gemma":0.01155387,"domain_scores_codex":[0.9997144,0.00009644315,0.00001276112,0.00003868309,0.00009886968,0.00003870131],"domain_scores_gemma":[0.9993342,0.0003355575,0.00005882204,0.0001050469,0.0001124727,0.00005392164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005034678,0.00005882616,0.0006443392,0.00007981268,0.00003874144,0.00006006992,0.00006581448,0.9664698,0.004460459,0.01307525,0.001583353,0.01341331],"study_design_scores_gemma":[0.00001321401,0.000009229504,0.00006385745,0.000005202739,0.000002837831,0.000005999055,0.000007735271,0.996092,0.0007772085,0.002203744,0.0008125904,0.000006290963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09136654,0.0004750559,0.8933797,0.0005925565,0.00009139935,0.0001824905,0.0006702821,0.003442581,0.009799344],"genre_scores_gemma":[0.423191,0.0004287871,0.5685404,0.0003168478,0.00003827216,0.0008479315,0.001269286,0.002024707,0.003342801],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008591608,"threshold_uncertainty_score":0.01708323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013210280731111,"score_gpt":0.254795092479543,"score_spread":0.241584811748432,"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."}}