{"id":"W2045288965","doi":"10.1021/ie020941f","title":"Digital Imaging for Online Monitoring and Control of Industrial Snack Food Processes","year":2003,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Principal component analysis; Computer science; Feature (linguistics); Coating; Process engineering; Product (mathematics); Control (management); Quality (philosophy); Digital imaging; Snack food; Pattern recognition (psychology); Artificial intelligence; Data mining; Image processing; Digital image; Image (mathematics); Chemistry; Engineering; Mathematics; Food science","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":[0.0004279691,0.0003519541,0.0002502273,0.000388687,0.0001751261,0.0004140366,0.0005272949,0.0002921094,0.001783621],"category_scores_gemma":[0.001185153,0.0001476505,0.0001273673,0.0002883908,0.0002060685,0.0003808387,0.0002721297,0.0003341941,0.0002791018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004506726,"about_ca_system_score_gemma":0.0002555925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001233366,"about_ca_topic_score_gemma":0.001460892,"domain_scores_codex":[0.9996454,0.00006989638,0.00001397584,0.00005127538,0.0001988978,0.00002062973],"domain_scores_gemma":[0.9993197,0.0003199292,0.0000764072,0.00006762998,0.0001884171,0.00002790939],"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":[0.0007084547,0.0002727671,0.003025527,0.0002879433,0.00002681031,0.00008779267,0.00008288075,0.0131272,0.5827154,0.001339334,0.001960018,0.3963659],"study_design_scores_gemma":[0.0001081865,0.0009304243,0.01280641,0.00002777164,0.00006766712,0.0003349467,0.00004210612,0.3321096,0.6404701,0.0008689587,0.0121778,0.00005595599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3279029,0.00257882,0.6558904,0.0004917001,0.0001762548,0.0002459337,0.0002738458,0.004682109,0.007758124],"genre_scores_gemma":[0.7588452,0.0007339052,0.236183,0.0001600497,0.00004297692,0.000125948,0.0001918255,0.0001167322,0.003600321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001783621,"threshold_uncertainty_score":0.005966783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09625862212565735,"score_gpt":0.3451832363464409,"score_spread":0.2489246142207836,"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."}}