{"id":"W2062848760","doi":"10.3390/molecules20034780","title":"QM/MM Calculations with deMon2k","year":2015,"lang":"en","type":"review","venue":"Molecules","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional; Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Ciencia y Tecnología; Grantová Agentura České Republiky; Western Canada Research Grid; Compute Canada","keywords":"Density functional theory; Biomolecule; Context (archaeology); Computer science; Molecular dynamics; Software; Code (set theory); Chemistry; Quantum; Computational science; Biological system; Nanotechnology; Computational chemistry; Physics; Materials science; Programming language; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005828405,0.0003218988,0.0007054586,0.00009554979,0.00008145017,0.00005099549,0.0003509426,0.0002648144,0.001460199],"category_scores_gemma":[0.00001432991,0.000239932,0.0002054945,0.0003438933,0.0000534783,0.00002308711,0.00007747733,0.0003250365,0.0001061413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001327353,"about_ca_system_score_gemma":0.000192524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002120979,"about_ca_topic_score_gemma":0.00000790691,"domain_scores_codex":[0.998855,0.0000156345,0.0003119172,0.0003679309,0.0002228497,0.0002266957],"domain_scores_gemma":[0.9988667,0.00003492717,0.000206212,0.0006960567,0.00006948997,0.0001265878],"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":[0.000001453426,0.0001006673,0.000004664006,0.005414901,0.0001721369,0.00002886987,0.0000104333,0.000001686584,0.00001599868,0.03189185,0.008245094,0.9541122],"study_design_scores_gemma":[0.0000466037,0.000009825215,2.207605e-7,0.001429774,0.0003681427,0.00005339093,0.000004397588,0.00001140027,0.00004159752,0.0006890856,0.997046,0.000299555],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001235327,0.844819,0.001240354,0.00002971203,0.000006702629,0.0001767264,0.0001158781,0.0002489434,0.1533614],"genre_scores_gemma":[0.00002184866,0.9870462,0.007508458,0.00001340131,0.0001135858,0.0005044263,0.0005517424,0.00008438384,0.004155884],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9888009,"threshold_uncertainty_score":0.9994526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04228024138647748,"score_gpt":0.3343554613191377,"score_spread":0.2920752199326603,"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."}}