{"id":"W2023587656","doi":"10.1002/adem.200400122","title":"Learning with METIS: An Interactive Learning Software for Materials Science","year":2004,"lang":"en","type":"article","venue":"Advanced Engineering Materials","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metis; Visualization; Relation (database); Software; Materials science; Human–computer interaction; Computer science; Artificial intelligence; World Wide Web; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004010608,0.0004735639,0.0005559,0.0003170702,0.000225432,0.0003198093,0.0003593411,0.0001110818,0.00006617107],"category_scores_gemma":[0.0004273246,0.0004742959,0.00002819133,0.0004094673,0.00009377672,0.002205522,0.00007196629,0.0001677207,0.00001528704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003190786,"about_ca_system_score_gemma":0.00005201405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006698854,"about_ca_topic_score_gemma":7.773609e-7,"domain_scores_codex":[0.9979773,0.00002534048,0.0005116818,0.0005256836,0.0002524585,0.0007075022],"domain_scores_gemma":[0.99903,0.00006987435,0.000157455,0.0003246884,0.0002567215,0.0001612511],"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":[0.00005952159,0.000009516487,0.000002291551,0.0001475441,0.0000151098,0.000003511982,0.0002158135,0.3719412,0.626556,0.0003024951,4.023101e-7,0.0007465587],"study_design_scores_gemma":[0.000764226,0.0004132401,0.0002510373,0.0003037593,0.00002038635,0.00002910277,0.00008830405,0.0002586035,0.9962435,0.0003340607,0.0006738598,0.00061997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6357632,0.00001512291,0.3599306,0.00000570684,0.0006756996,0.0005111262,0.00004940755,0.003036378,0.00001270272],"genre_scores_gemma":[0.8028021,0.00004990524,0.1960779,0.00001337221,0.0001629677,0.0004943012,0.000164075,0.0002141504,0.00002116965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3716826,"threshold_uncertainty_score":0.9997709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004545052174979233,"score_gpt":0.2284728328598444,"score_spread":0.2239277806848652,"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."}}