{"id":"W2039636496","doi":"10.1017/s143192761005796x","title":"Advanced Structural and Chemical Analysis of Materials for Energy Related Applications","year":2010,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Microanalysis; Materials science; Chemistry","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":[0.0001383636,0.0001719431,0.0001352636,0.0006271526,0.0002592198,0.0002275411,0.0002978801,0.0002222063,0.01371651],"category_scores_gemma":[0.0001769385,0.0001231099,0.0001341993,0.0002865193,0.0001644216,0.0003185363,0.0001945885,0.0002943161,0.001065594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002557459,"about_ca_system_score_gemma":0.0002038878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009877858,"about_ca_topic_score_gemma":0.003414649,"domain_scores_codex":[0.9999075,0.000005191685,0.000002693896,0.00001219863,0.00006246659,0.000009879201],"domain_scores_gemma":[0.999939,0.00001057421,0.000005644659,0.000009415722,0.00002924867,0.000006227461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009340334,0.00004171841,0.0007725175,0.0001854153,0.00002034894,0.00007744302,0.00003023137,0.0008777683,0.9650561,0.003273801,0.005137147,0.02443412],"study_design_scores_gemma":[0.00001738965,0.0001232456,0.01120575,0.00001400526,0.0000352005,0.0003154729,0.00005546981,0.008593127,0.9243264,0.002096114,0.05320393,0.00001391927],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7429826,0.01503507,0.1090798,0.00202411,0.001448263,0.0002707691,0.007926469,0.001055665,0.1201773],"genre_scores_gemma":[0.8731635,0.004908468,0.03806171,0.0002314267,0.0001892061,0.00009622106,0.004840367,0.0001592608,0.07834992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01371651,"threshold_uncertainty_score":0.04588634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002862023617433809,"score_gpt":0.2376732798281816,"score_spread":0.2348112562107477,"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."}}