{"id":"W4240297320","doi":"10.1002/cphc.201600577","title":"Molecular Machines","year":2016,"lang":"en","type":"editorial","venue":"ChemPhysChem","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Chemistry; Nanotechnology; Materials science","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008676864,0.0006715524,0.0005730588,0.00003471513,0.0001134891,0.00003988068,0.0009076223,0.001386316,0.005253715],"category_scores_gemma":[0.0005657262,0.0005951203,0.0003187469,0.00006893099,0.0001882964,0.0001023051,0.000232647,0.001017043,0.0004296801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003791934,"about_ca_system_score_gemma":0.0002737422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002141391,"about_ca_topic_score_gemma":2.196533e-7,"domain_scores_codex":[0.9972874,0.000007955357,0.0004310363,0.0009032484,0.0008309162,0.0005394644],"domain_scores_gemma":[0.9978371,0.0002816684,0.0003307771,0.001180063,0.0001691303,0.0002013192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001889214,0.00004297177,0.000001715978,0.0006119032,0.00007564756,0.00005287822,0.00001141427,4.514641e-7,0.3768209,0.00001186231,0.6196874,0.002663942],"study_design_scores_gemma":[0.0003647481,0.000002573612,6.627382e-9,0.000263612,0.00003619335,0.00000109951,0.000002696743,0.000001205233,0.4501507,0.000148571,0.5486115,0.0004170738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.001526407,0.001639872,0.00005164929,0.00003942653,0.6931855,0.0000458096,0.0006731607,0.0003453914,0.3024928],"genre_scores_gemma":[0.0005115172,0.0001596034,0.0002605812,0.00003595727,0.8981787,0.00008487467,0.001012443,0.0001899806,0.09956636],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.2049932,"threshold_uncertainty_score":0.9999101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005830186225859094,"score_gpt":0.2589603010673784,"score_spread":0.2531301148415194,"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."}}