{"id":"W4385490840","doi":"10.1016/j.matt.2023.06.046","title":"35+1 challenges in materials science being tackled by PIs under 35(ish) in 2023","year":2023,"lang":"en","type":"article","venue":"Matter","topic":"Inorganic Chemistry and Materials","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Materials science; Engineering ethics; Nanotechnology; Engineering","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004974717,0.0001740512,0.0002513374,0.00008933804,0.00005955275,0.000112022,0.0003581453,0.0001381722,0.01287458],"category_scores_gemma":[0.00004052562,0.0001773228,0.00002224721,0.0002820805,0.0001039629,0.0001560128,0.000233545,0.0001071707,0.001440504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00012082,"about_ca_system_score_gemma":0.00004085033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009895803,"about_ca_topic_score_gemma":0.00001502886,"domain_scores_codex":[0.9984561,0.00001809965,0.0003397888,0.000444255,0.0002197148,0.0005220824],"domain_scores_gemma":[0.9994609,0.00004767779,0.00006583409,0.0003545101,0.00001672807,0.00005430876],"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":[0.00001302117,0.00002882489,0.000497799,0.0003017351,0.000003686834,0.00003819951,0.0004237796,0.000001981482,0.9934389,0.00004771608,0.005136698,0.00006764413],"study_design_scores_gemma":[0.0004119752,0.00000231919,0.002386841,0.0001492962,0.000003416808,0.000009393577,0.0003226881,0.000002362025,0.9930947,0.0008237485,0.002576331,0.0002168592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707247,0.00005383222,5.70227e-7,0.002328008,0.0002373561,0.00005229006,0.00004292313,0.00008136509,0.02647893],"genre_scores_gemma":[0.9919323,0.0001492074,0.00001521726,0.0003955208,0.0001448132,0.00004080862,0.00004469583,0.00003141647,0.007246056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02120754,"threshold_uncertainty_score":0.999337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02194353285448756,"score_gpt":0.2531475832127005,"score_spread":0.231204050358213,"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."}}