{"id":"W2559828041","doi":"10.1017/s143192761600951x","title":"TEM Characterization of HSLA Steels and Welds","year":2016,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Microstructure and Mechanical Properties of Steels","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Characterization (materials science); Materials science; Metallurgy; Nanotechnology","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":[0.0002084802,0.0002048361,0.0001553016,0.0006394784,0.0004316901,0.0001952244,0.0002119389,0.0002861949,0.001989199],"category_scores_gemma":[0.0002864813,0.000150757,0.0001532801,0.0003375212,0.0002024741,0.0002026429,0.0001281996,0.0001845066,0.000521181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002116931,"about_ca_system_score_gemma":0.0001879011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002340803,"about_ca_topic_score_gemma":0.0038518,"domain_scores_codex":[0.9998608,0.000007169008,0.00001328605,0.0000255348,0.00007597795,0.00001730142],"domain_scores_gemma":[0.9996769,0.00002494365,0.00004842205,0.00002220795,0.0002050022,0.0000225163],"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":[0.00003530626,0.000004079703,0.0004497301,0.00005210722,0.000003333938,0.000101673,0.00008235512,0.0001366512,0.9964439,0.00008661795,0.0001603209,0.0024439],"study_design_scores_gemma":[0.000005715196,0.0001394017,0.03456385,0.00002343646,0.00001697452,0.0005557714,0.0002555991,0.002076731,0.9540812,0.0000744381,0.008193925,0.00001304238],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973345,0.002284762,0.01657268,0.0001223454,0.00004660389,0.00004886221,0.001288097,0.0004017125,0.005889849],"genre_scores_gemma":[0.9770393,0.000684165,0.01292751,0.00007272158,0.00001310438,0.00003562935,0.001260654,0.00009187549,0.007874983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002340803,"threshold_uncertainty_score":0.006654501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005625432965903013,"score_gpt":0.1960552538061129,"score_spread":0.1904298208402099,"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."}}