{"id":"W2802911546","doi":"10.1364/cleo_at.2018.atu4m.4","title":"Tracking the Morphology Evolution of 3D Selective Laser Melting in situ using Inline Coherent Imaging","year":2018,"lang":"en","type":"article","venue":"Conference on Lasers and Electro-Optics","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Selective laser melting; In situ; Interferometry; Materials science; Tracking (education); Morphology (biology); Laser; Optics; Geology; Physics","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":[0.0001592546,0.0002473663,0.0001886535,0.0003501355,0.0001923285,0.0005243796,0.0004695764,0.0004102386,0.0008230621],"category_scores_gemma":[0.0002891581,0.0002274147,0.0001595333,0.0003274413,0.0003145135,0.0004396786,0.0003602085,0.0004212612,0.0002074443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004403397,"about_ca_system_score_gemma":0.000277109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001303399,"about_ca_topic_score_gemma":0.003343617,"domain_scores_codex":[0.9998673,0.000009736394,0.000005862249,0.00002914801,0.00005843603,0.00002955982],"domain_scores_gemma":[0.9996828,0.00006023579,0.0001407452,0.0000373847,0.0000574935,0.00002146766],"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":[0.00002467957,0.00001147549,0.0006483108,0.00001718079,0.000002650393,0.00003481725,0.00007405682,0.0004230338,0.9959195,0.0001249076,0.00005402855,0.002665391],"study_design_scores_gemma":[0.000003783077,0.00004840487,0.002413451,0.000002986183,0.000006020307,0.00005192322,0.0000437948,0.01169862,0.9850929,0.00003672425,0.0005935704,0.000007852021],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739695,0.000349964,0.02336759,0.00009552786,0.00001559646,0.00001751558,0.0001744618,0.0002575039,0.001752384],"genre_scores_gemma":[0.9617555,0.0003880849,0.03624822,0.00005914577,0.00001036968,0.00003234048,0.0001414294,0.00005625217,0.001308741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001303399,"threshold_uncertainty_score":0.003194928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776345757555683,"score_gpt":0.244977339320827,"score_spread":0.2272138817452702,"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."}}