{"id":"W4385510615","doi":"10.31399/asm.amp.2021-07.p041","title":"Selective Laser Processing for Functionally Graded Shape Memory Alloy Medical Devices: Process and Applications in Dentistry","year":2021,"lang":"en","type":"article","venue":"AM&P Technical Articles","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Smarter Alloys (Canada)","funders":"","keywords":"Shape-memory alloy; Materials science; Process (computing); Grading (engineering); Dentistry; Computer science; Engineering drawing; Metallurgy; Engineering; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0002373586,0.0001591839,0.0002043762,0.0000612017,0.0001010262,0.00009678138,0.0001725278,0.0001770399,0.00003745175],"category_scores_gemma":[0.0002368025,0.000152926,0.00003318889,0.0004173402,0.0001149715,0.0002615159,0.0000687098,0.0001941059,0.000003803949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005559494,"about_ca_system_score_gemma":0.0001063748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004176692,"about_ca_topic_score_gemma":0.0001501239,"domain_scores_codex":[0.9988022,0.00002157857,0.0003325337,0.0003245087,0.0002459137,0.0002732521],"domain_scores_gemma":[0.9994193,0.0001499002,0.00003815022,0.0001414382,0.0001359128,0.0001152467],"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":[0.0002544654,0.00205635,0.02858476,0.009801524,0.0002232285,0.0001864052,0.001042107,0.002170508,0.7285584,0.005330621,0.004192112,0.2175995],"study_design_scores_gemma":[0.001606091,0.0001065605,0.02994463,0.0008580764,0.0001047561,0.0002883532,0.0005618969,0.05447755,0.8621188,0.0470693,0.001851536,0.001012423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856668,0.0004307575,0.01149825,0.0004235651,0.0000449615,0.0004486297,0.0000102582,0.001232793,0.0002439837],"genre_scores_gemma":[0.99288,0.00002245617,0.006045976,0.000180393,0.00008793346,0.0007052267,0.00002290625,0.00003978587,0.00001528194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2165871,"threshold_uncertainty_score":0.6236141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0132370789652299,"score_gpt":0.2685034904035821,"score_spread":0.2552664114383522,"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."}}