{"id":"W2889781812","doi":"10.1016/j.jmapro.2018.09.018","title":"Metallurgical features of direct laser-deposited Ti6Al4V with trace boron","year":2018,"lang":"en","type":"article","venue":"Journal of Manufacturing Processes","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Australian Research Council; M.S.I. Foundation","keywords":"Materials science; Microstructure; Boron; Indentation hardness; Metallurgy; Martensite; Titanium alloy; Deposition (geology); Laser; Alloy; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002142686,0.0002895842,0.0005444458,0.0001862053,0.00008031457,0.00008534184,0.0003179996,0.00009880163,0.0002007576],"category_scores_gemma":[0.00008690319,0.0001951412,0.0000815946,0.0001462093,0.0001416444,0.0004063453,0.00003165005,0.0002291188,0.000006969391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003206595,"about_ca_system_score_gemma":0.00006807247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009336663,"about_ca_topic_score_gemma":0.00002839469,"domain_scores_codex":[0.9986258,0.0000307153,0.0005000542,0.000162889,0.0003977577,0.0002828331],"domain_scores_gemma":[0.9988561,0.0001720816,0.0003596616,0.0001543558,0.0003409759,0.0001167742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.02394578,0.004203878,0.002536104,0.09691038,0.01739753,0.003814223,0.02731309,0.4534177,0.173877,0.0001546586,0.0538338,0.1425958],"study_design_scores_gemma":[0.0004654657,0.0005533441,0.005224793,0.000403609,0.0001209672,0.0002869278,0.00007377185,0.000006972758,0.978754,0.00007083172,0.01379705,0.0002422039],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917846,0.001579575,0.001389657,0.00006137941,0.0003021058,0.0000946669,0.00001981408,0.0001150708,0.004653131],"genre_scores_gemma":[0.9972801,0.0003664825,0.001588883,0.00002004784,0.0005210955,0.000003525522,0.000002744623,0.00005450263,0.0001626422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.804877,"threshold_uncertainty_score":0.7957625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008252092288997178,"score_gpt":0.2136290103832127,"score_spread":0.2053769180942155,"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."}}