{"id":"W4402269723","doi":"10.1364/cleo_at.2024.am1c.3","title":"Preliminary Development of Thermographic Monitoring of the Laser Remelting Process","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Western University","funders":"","keywords":"Process (computing); Laser; Process development; Materials science; Thermography; Computer science; Process engineering; Engineering; Infrared; Optics","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":[0.001110691,0.0004186209,0.0003637253,0.0007815388,0.0002403764,0.0005013769,0.0006682125,0.0006178354,0.001108606],"category_scores_gemma":[0.001489708,0.0002502376,0.0003331527,0.0004325482,0.0002660793,0.0005863145,0.0002701993,0.0005184937,0.000326764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002919924,"about_ca_system_score_gemma":0.0004742016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008409952,"about_ca_topic_score_gemma":0.001070165,"domain_scores_codex":[0.9994885,0.00008614377,0.0000281273,0.00009778503,0.0002672849,0.00003222241],"domain_scores_gemma":[0.9989417,0.0003020005,0.00008068409,0.0001326607,0.0004878047,0.00005517437],"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":[0.0001559307,0.00006347065,0.001706362,0.0002499634,0.00001035983,0.00006480928,0.0001380461,0.0009292616,0.9504697,0.0004571225,0.0002002099,0.04555491],"study_design_scores_gemma":[0.000007917884,0.0007137482,0.01040754,0.00002230282,0.00002927683,0.0002455111,0.00005299449,0.008693413,0.9744856,0.0001377084,0.005183849,0.0000201578],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.317136,0.003779335,0.668555,0.0002800396,0.0001568595,0.0006151928,0.0007944545,0.001783463,0.006899686],"genre_scores_gemma":[0.7850755,0.001654138,0.2067046,0.00008133791,0.00006328582,0.0002612532,0.0004510267,0.0001530971,0.005555713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001110691,"threshold_uncertainty_score":0.005873978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009619363311835239,"score_gpt":0.2438417902021488,"score_spread":0.2342224268903136,"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."}}