{"id":"W2551561503","doi":"10.1039/c6cc05497h","title":"Molecular tuning of amino acids to form two-dimensional molecular networks driven by conformational preorganization","year":2016,"lang":"en","type":"article","venue":"Chemical Communications","topic":"Surface Chemistry and Catalysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Intramolecular force; Chemistry; Molecular conformation; Molecular dynamics; Stereochemistry; Crystallography; Biophysics; Molecule; Computational chemistry; Organic chemistry; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006457671,0.000119488,0.0001394144,0.00003148108,0.00004992001,0.00001152246,0.0005316493,0.00008452369,0.00005537671],"category_scores_gemma":[0.00008274998,0.0001116182,0.00005838272,0.000269397,0.00008883159,0.0001219906,0.0002122979,0.0001124987,0.00001852466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007527558,"about_ca_system_score_gemma":0.00001552563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001422599,"about_ca_topic_score_gemma":2.791659e-7,"domain_scores_codex":[0.9992939,0.00001393543,0.0002785316,0.0001043669,0.0001535554,0.0001557413],"domain_scores_gemma":[0.9988278,0.0001231986,0.00004708875,0.000755123,0.0001413782,0.0001053869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002735499,0.00002180564,0.0001510851,0.000009450869,0.00004481736,1.397643e-7,0.00006109211,0.01470613,0.9835968,0.0003785815,0.0004382333,0.0005891026],"study_design_scores_gemma":[0.0002379641,0.000004209991,0.00002691678,0.00004257627,0.00002541315,0.000002354108,0.00001560007,0.02693551,0.9719748,0.0001166082,0.0004745496,0.0001434776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9112058,0.0003614327,0.08524778,0.0004668419,0.00002107385,0.0001134109,0.00005309365,0.0001333098,0.002397226],"genre_scores_gemma":[0.9959048,0.00002034354,0.003364261,0.00007639622,0.000008389955,0.00003062221,0.0005495141,0.00002232267,0.00002334832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08469897,"threshold_uncertainty_score":0.4551659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006272143909948099,"score_gpt":0.2139730474870207,"score_spread":0.2077009035770726,"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."}}