{"id":"W2983323169","doi":"10.1039/c9cp03103k","title":"A shared-weight neural network architecture for predicting molecular properties","year":2019,"lang":"en","type":"article","venue":"Physical Chemistry Chemical Physics","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health PEI; University of Prince Edward Island","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Artificial neural network; Architecture; Computer science; Computer architecture; Artificial intelligence; Biological system; Chemistry; Biology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005188012,0.0006117958,0.0004821819,0.0002728941,0.0003110049,0.000402552,0.001735004,0.0008992502,0.002329107],"category_scores_gemma":[0.00129937,0.0002745612,0.0003900045,0.0004143817,0.0004730438,0.001101426,0.0007079628,0.0009876894,0.0005679769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006386583,"about_ca_system_score_gemma":0.0008354775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006920083,"about_ca_topic_score_gemma":0.00941898,"domain_scores_codex":[0.9998386,0.00002844354,0.000008128282,0.00005164757,0.00005058451,0.00002260746],"domain_scores_gemma":[0.999655,0.0001020769,0.00002895425,0.00006207933,0.0001341214,0.00001778537],"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":[0.0001249919,0.00009478138,0.001035508,0.00005196128,0.00006250696,0.00005457942,0.00002382936,0.8379615,0.007943471,0.00728147,0.001883147,0.1434823],"study_design_scores_gemma":[0.000002443614,0.00001307638,0.00005158127,0.000001158781,0.000003481923,0.000004222942,0.000001119222,0.9979924,0.000727782,0.001084017,0.0001167194,0.00000203576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1710675,0.0005533026,0.8201293,0.0005786964,0.0001273917,0.00006465834,0.0003195097,0.001700733,0.005458816],"genre_scores_gemma":[0.8563424,0.0002053573,0.137109,0.0001195959,0.00004371362,0.0001148225,0.0004990551,0.000052661,0.005513394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006920083,"threshold_uncertainty_score":0.01375955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008834111510753579,"score_gpt":0.2285704188956648,"score_spread":0.2197363073849113,"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."}}