{"id":"W2066475355","doi":"10.1364/ao.51.000610","title":"Application of the Hough transform for the automatic determination of soot aggregate morphology","year":2012,"lang":"en","type":"article","venue":"Applied Optics","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"","keywords":"Aggregate (composite); Hough transform; Image processing; Materials science; Optics; Particle (ecology); Resolution (logic); Computer science; Soot; Digital image processing; Laptop; Image (mathematics); Artificial intelligence; Nanotechnology; Physics; Chemistry","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":[0.001149811,0.0007278142,0.0006394775,0.002198927,0.0004727418,0.00091216,0.0009314994,0.0007552311,0.001393126],"category_scores_gemma":[0.002475935,0.0005780284,0.0004888335,0.001795994,0.0006419852,0.001312374,0.0008797374,0.0008426046,0.0008882487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004240573,"about_ca_system_score_gemma":0.0006314935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00138605,"about_ca_topic_score_gemma":0.001801803,"domain_scores_codex":[0.9986198,0.0002053657,0.00005959408,0.0002045801,0.00084784,0.0000627366],"domain_scores_gemma":[0.9984844,0.0005853623,0.0001234881,0.000224279,0.0005406928,0.00004182511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002139056,0.00009493023,0.00247895,0.0002315332,0.00009504164,0.0001855272,0.0002904994,0.01386373,0.421629,0.003595291,0.002211975,0.5551096],"study_design_scores_gemma":[0.0000232167,0.0001436105,0.005613161,0.00001439895,0.00005751928,0.0007928589,0.0000932725,0.4810085,0.4963445,0.003160842,0.01265555,0.00009259803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01492702,0.0001794065,0.982969,0.00004536097,0.00004026047,0.00004091829,0.00004471618,0.00111959,0.0006337185],"genre_scores_gemma":[0.1045033,0.0002864503,0.8939868,0.00002290541,0.00002482828,0.00006356714,0.0001322031,0.0001545304,0.0008254214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002198927,"threshold_uncertainty_score":0.006080866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009987929108777495,"score_gpt":0.2457670655047062,"score_spread":0.2357791363959287,"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."}}