{"id":"W4237273346","doi":"10.1007/s10751-007-9574-8","title":"Foreword","year":2006,"lang":"en","type":"article","venue":"Hyperfine Interactions","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba; TRIUMF","funders":"","keywords":"Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005242108,0.0001126224,0.0001015118,0.0001704035,0.0001272182,0.00003146081,0.0001040854,0.00002542395,0.003127213],"category_scores_gemma":[0.00004994947,0.0001095617,0.00008537668,0.0003199246,0.00003627348,0.0002903367,0.00003013722,0.0001799293,0.02437118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009103469,"about_ca_system_score_gemma":0.00001901658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005827248,"about_ca_topic_score_gemma":0.001247148,"domain_scores_codex":[0.9992512,0.00002229346,0.0001998297,0.0001798654,0.0001270726,0.0002196819],"domain_scores_gemma":[0.9994652,0.00006554933,0.00005829484,0.0002731177,0.0000953277,0.00004253492],"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":[0.00004364256,0.0004613053,0.009325949,0.000004856556,0.00003401094,0.00001702135,0.00004440345,0.0005378493,0.1531688,0.01884415,0.8155443,0.001973696],"study_design_scores_gemma":[0.0002692652,0.00002077054,0.02363923,0.0000153138,0.00002710706,0.0001636151,0.00005674931,0.001770712,0.008017513,0.001182735,0.9646738,0.0001631458],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7223154,0.00007015413,0.00132509,0.001469366,0.0008820702,0.0001478317,0.0001531765,0.0006192477,0.2730177],"genre_scores_gemma":[0.9642311,6.071365e-7,0.001398827,0.0001309924,0.0005773204,0.00004188781,0.00007079356,0.00005175043,0.03349667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2419157,"threshold_uncertainty_score":0.9977841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01457696676788042,"score_gpt":0.2705232384042654,"score_spread":0.255946271636385,"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."}}