{"id":"W4229014034","doi":"10.1021/acscentsci.2c00041","title":"High-Throughput Evaluation of Emission and Structure in Reduced-Dimensional Perovskites","year":2022,"lang":"en","type":"article","venue":"ACS Central Science","topic":"Perovskite Materials and Applications","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network; Vector Institute; University of Ottawa; Princess Margaret Cancer Centre; The Scarborough Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Total; University of Toronto; LG Electronics; Canada Foundation for Innovation; Government of Canada; Government of Ontario","keywords":"Photoluminescence; Workflow; Computer science; Materials science; Leverage (statistics); Nanotechnology; Quantum yield; Characterization (materials science); Optoelectronics; Artificial intelligence; Physics; Fluorescence; Optics; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.000329128,0.00005013739,0.00006359356,0.00004793734,0.000119194,0.00001618478,0.0001191906,0.00001294171,0.0001703388],"category_scores_gemma":[0.00002501578,0.00004648442,0.000005951955,0.0003208699,0.0000779277,0.0001184596,0.00007946426,0.00005579893,3.130607e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001074668,"about_ca_system_score_gemma":0.00006024752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004531059,"about_ca_topic_score_gemma":0.000005292273,"domain_scores_codex":[0.9991769,0.00001909787,0.0001138701,0.0001400291,0.0003896257,0.00016052],"domain_scores_gemma":[0.9998004,0.00001118512,0.00002106597,0.00009523676,0.00003050505,0.00004161985],"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":[0.000001382774,0.000007644078,0.0004851284,0.000004232314,5.984267e-7,1.28879e-7,0.0001861765,0.06886855,0.9274519,0.0004485595,0.00008122725,0.002464456],"study_design_scores_gemma":[0.0003896491,0.0000266207,0.2937728,0.00001601658,0.00001068156,0.000009617766,0.0001391703,0.07359578,0.627997,0.003560684,0.0003254648,0.0001564518],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993685,0.0001424167,0.000006252936,0.00009337864,0.000172408,0.000112376,0.00003149791,0.00001662708,0.00005657561],"genre_scores_gemma":[0.9995619,0.000009372172,0.0003690468,0.00001231768,0.00001754077,0.00001115366,0.00001119481,0.000003654537,0.000003813556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2994549,"threshold_uncertainty_score":0.189558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108994932815785,"score_gpt":0.2432235780680933,"score_spread":0.2323240847865148,"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."}}