{"id":"W4323644453","doi":"10.59082/yaej8738","title":"Editorial | A Homecoming for Microscopists","year":2022,"lang":"en","type":"article","venue":"The Microscope","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homecoming; Quarter (Canadian coin); Coronavirus disease 2019 (COVID-19); Pandemic; Schedule; History; Medicine; Art history; Management; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005038018,0.002355624,0.001840289,0.002796378,0.00390346,0.005799675,0.00343143,0.01150107,0.0468696],"category_scores_gemma":[0.01548112,0.001292582,0.002988089,0.0007839836,0.002040896,0.003886337,0.001804403,0.01812874,0.03288695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002793225,"about_ca_system_score_gemma":0.003050878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002035994,"about_ca_topic_score_gemma":0.006876121,"domain_scores_codex":[0.9967389,0.0003618857,0.0002297302,0.0004100139,0.001955339,0.0003043007],"domain_scores_gemma":[0.9895761,0.002206098,0.0005888907,0.0005463995,0.004120904,0.002961542],"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":[0.00002140169,0.00001034867,0.00001371351,0.00005693908,0.00000552502,0.00006146047,0.000004417577,0.000009331126,0.0001040413,0.0001984356,0.9957353,0.00377911],"study_design_scores_gemma":[0.00001994745,0.0000230674,0.0001610681,0.00008158457,0.000009158965,0.0001529819,0.00002363754,0.00004894428,0.0001155331,0.0003475391,0.9990063,0.00001029176],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00006132036,0.002818848,0.0002244968,0.04523052,0.9481666,0.00003785743,0.00008367746,0.0002247299,0.003151984],"genre_scores_gemma":[0.0007412471,0.003120212,0.000300425,0.04246813,0.9185177,0.00005157057,0.0000890763,0.0001152541,0.03459647],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0468696,"threshold_uncertainty_score":0.1567944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008533807752373333,"score_gpt":0.2672943513466683,"score_spread":0.258760543594295,"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."}}