{"id":"W3031363365","doi":"10.1039/d0sc00982b","title":"Pushing property limits in materials discovery<i>via</i>boundless objective-free exploration","year":2020,"lang":"en","type":"article","venue":"Chemical Science","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"Core Research for Evolutional Science and Technology; RIKEN; Exploratory Research for Advanced Technology; National Institute for Materials Science; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Property (philosophy); Computer science; Astrobiology; Physics; Philosophy; Epistemology","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":[0.002929945,0.0008957278,0.001155164,0.0009813131,0.000562437,0.001198046,0.00139488,0.001321847,0.001717645],"category_scores_gemma":[0.007932357,0.0006047244,0.0008796804,0.0005443033,0.002034398,0.002049335,0.002197452,0.001209829,0.0003329948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008978602,"about_ca_system_score_gemma":0.001474761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001808781,"about_ca_topic_score_gemma":0.001730877,"domain_scores_codex":[0.9991756,0.0004088279,0.00003840031,0.00009554077,0.0002107301,0.00007094038],"domain_scores_gemma":[0.9963379,0.002749226,0.0002675281,0.0002858016,0.0002493056,0.0001103613],"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":[0.0001842022,0.0001048779,0.00134945,0.0001488956,0.00007302524,0.00008271743,0.00009522943,0.9067916,0.003300557,0.03638592,0.001267437,0.05021605],"study_design_scores_gemma":[0.00001552944,0.00004034036,0.00006368328,0.000007130078,0.000004579843,0.00001318027,0.000006970478,0.9877658,0.0006252239,0.01114789,0.0003050516,0.000004692557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06356227,0.0004905651,0.93145,0.0005854354,0.00002896951,0.00006742721,0.00005321675,0.0005894421,0.003172696],"genre_scores_gemma":[0.6743984,0.0002484696,0.3218732,0.0003938229,0.00004137449,0.000277823,0.0001723863,0.0001805716,0.002413966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002929945,"threshold_uncertainty_score":0.01549518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0295549709824757,"score_gpt":0.2614848664078177,"score_spread":0.231929895425342,"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."}}