{"id":"W4294703831","doi":"10.31399/asm.cp.itsc2007p0832","title":"Optimization of Sensor Optics for Industrial Thermal Spray Sensors","year":2007,"lang":"en","type":"article","venue":"Thermal spray","topic":"Fluid Dynamics and Heat Transfer","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Process (computing); Lens (geology); Measure (data warehouse); Image resolution; Computer science; Resolution (logic); Field (mathematics); Thermal; Volume (thermodynamics); Mechanical engineering; Optics; Engineering; Physics; Computer vision; Artificial intelligence; Mathematics","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":[0.001080357,0.001064342,0.0005043179,0.0005378862,0.0004161101,0.001101832,0.0007534681,0.0007758899,0.002220759],"category_scores_gemma":[0.00249541,0.000613977,0.0004462018,0.0005639717,0.0007645605,0.001127712,0.0005596151,0.0005281742,0.0004901757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002179589,"about_ca_system_score_gemma":0.0009687412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001261201,"about_ca_topic_score_gemma":0.002148115,"domain_scores_codex":[0.9990407,0.0001228482,0.00005312719,0.0002055271,0.0004914224,0.00008646511],"domain_scores_gemma":[0.9983053,0.000607829,0.0003499703,0.0001514065,0.0005289108,0.00005653414],"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":[0.0003532869,0.0001256945,0.001740873,0.0003820051,0.00003697423,0.00006022747,0.00007967682,0.01850468,0.9552708,0.003858034,0.0007394184,0.01884837],"study_design_scores_gemma":[0.0001475291,0.0005400531,0.003915963,0.00003622501,0.00008022282,0.0001831703,0.00009692827,0.08097778,0.9051234,0.0009652553,0.007848701,0.00008478942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5463843,0.0024342,0.4346302,0.0009277571,0.0002425468,0.0005181023,0.0003339344,0.001196345,0.01333263],"genre_scores_gemma":[0.6789241,0.001007418,0.3171306,0.0001463334,0.00003407345,0.0002249779,0.0002169945,0.0001954875,0.002119984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002220759,"threshold_uncertainty_score":0.01581413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937961552292115,"score_gpt":0.224234148641815,"score_spread":0.2048545331188938,"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."}}