{"id":"W4254256506","doi":"10.1557/mrc.2014.16","title":"MRC volume 4 issue 2 Cover and Front matter","year":2014,"lang":"en","type":"article","venue":"MRS Communications","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Sandia National Laboratories; Division of Materials Research; University of California, Santa Barbara; University of Waterloo; Johns Hopkins University; University of Cambridge; Northwestern University; École Polytechnique Fédérale de Lausanne; University of New South Wales; University of Pennsylvania","keywords":"Front cover; Materials science; Cover (algebra); Volume (thermodynamics); Front (military); Content (measure theory); Action (physics); Mechanical engineering; Thermodynamics; Engineering; Physics; Mathematics; Mathematical analysis","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007170796,0.001163622,0.0008456615,0.00298711,0.001680447,0.005152716,0.0011951,0.003271403,0.8185282],"category_scores_gemma":[0.00287085,0.0004568007,0.0009248741,0.001617644,0.0007668681,0.001708516,0.002611716,0.001720053,0.7140147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001847386,"about_ca_system_score_gemma":0.001999894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002485956,"about_ca_topic_score_gemma":0.005863056,"domain_scores_codex":[0.9990512,0.00008275539,0.00003836954,0.0001578108,0.0005092092,0.000160681],"domain_scores_gemma":[0.9980025,0.0002465415,0.0001366825,0.0002647927,0.0007169585,0.0006326328],"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":[0.00007293802,0.00003160468,0.0001130184,0.000202992,0.000008222188,0.0001507989,0.00001926535,0.00007709795,0.001013448,0.00183422,0.9340979,0.06237856],"study_design_scores_gemma":[0.000007665461,0.00002355667,0.0005013497,0.00007153167,0.000004334419,0.0001021329,0.00002228175,0.00003961521,0.0003007211,0.0003962013,0.9985267,0.000003938007],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001413331,0.003924297,0.0005829841,0.009488991,0.02261689,0.00009477363,0.002040759,0.001114479,0.9587235],"genre_scores_gemma":[0.002454972,0.001114719,0.0001620502,0.0006746218,0.003492373,0.00001487157,0.0005062573,0.0001988512,0.9913812],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1814718,"threshold_uncertainty_score":0.2588475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03653477153667174,"score_gpt":0.2171403302368048,"score_spread":0.1806055587001331,"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."}}