{"id":"W3167831955","doi":"10.71781/10723","title":"Identifying electrons with deep learning methods","year":2020,"lang":"en","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut de Valorisation des Données; Compute Canada","keywords":"Computer science; Artificial intelligence; Data science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0007797289,0.001038023,0.0006982021,0.001065005,0.0006577098,0.001942343,0.001515913,0.001738909,0.009388487],"category_scores_gemma":[0.003195694,0.0005227577,0.001050415,0.0007562296,0.0006303444,0.002632563,0.00189234,0.002435497,0.00301783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007257565,"about_ca_system_score_gemma":0.0008196727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002530194,"about_ca_topic_score_gemma":0.004250083,"domain_scores_codex":[0.9995795,0.00007313838,0.00002419762,0.0001169969,0.0001449629,0.00006117466],"domain_scores_gemma":[0.999238,0.0003814456,0.00005894497,0.000106801,0.0001729153,0.00004187001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003552123,0.0001496232,0.003830393,0.0006344645,0.0001535516,0.0003918441,0.0003044865,0.2222323,0.01356934,0.09250902,0.02697485,0.638895],"study_design_scores_gemma":[0.0000193387,0.00006193226,0.0006873338,0.0001283086,0.00003015941,0.0001614507,0.00008740681,0.8810632,0.01019032,0.08340638,0.02413256,0.00003153317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02829771,0.003308344,0.9476492,0.002188219,0.0007740401,0.00008744017,0.0006488499,0.002750042,0.01429607],"genre_scores_gemma":[0.448972,0.004344465,0.4772081,0.001644216,0.0006393186,0.0002447378,0.002828462,0.0006454247,0.06347337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009388487,"threshold_uncertainty_score":0.03140759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007397737244404415,"score_gpt":0.2379717373914645,"score_spread":0.2305740001470601,"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."}}