{"id":"W2045283192","doi":"10.1016/j.lwt.2007.02.022","title":"Early detection of apple bruises on different background colors using hyperspectral imaging","year":2007,"lang":"en","type":"article","venue":"LWT","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":270,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; McGill University","funders":"","keywords":"Hyperspectral imaging; Multispectral image; Bruise; Dimensionality reduction; Artificial intelligence; Wavelength; Remote sensing; Computer science; Computer vision; Pattern recognition (psychology); Optics; Physics; Geology; Medicine","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":[0.0001415562,0.0002973055,0.0003270772,0.0007349464,0.0002230932,0.0005000241,0.0001825775,0.0005272359,0.0009964007],"category_scores_gemma":[0.0002660169,0.000262526,0.0001998977,0.0003068337,0.0002338342,0.0004736308,0.0001952717,0.0006899245,0.0003823757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001791735,"about_ca_system_score_gemma":0.0001071633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009230505,"about_ca_topic_score_gemma":0.002335499,"domain_scores_codex":[0.9998934,0.0000105373,0.000001919572,0.00003083828,0.00003947869,0.00002381432],"domain_scores_gemma":[0.9997246,0.0000716235,0.00004929616,0.00001511568,0.0000795267,0.00005985857],"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":[0.0002665903,0.00004467127,0.00899963,0.000035537,0.00001288197,0.00006239901,0.00005234982,0.0001377164,0.9791276,0.0000459897,0.0001073134,0.01110732],"study_design_scores_gemma":[0.00001743772,0.0002462376,0.3949012,0.00001330261,0.00006536955,0.0005216551,0.000220243,0.0121146,0.5904849,0.0001966378,0.001187066,0.0000313847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846628,0.0003848089,0.01256399,0.00006568393,0.00002423205,0.00001884514,0.0001256088,0.0001679938,0.001986126],"genre_scores_gemma":[0.9820839,0.0002591955,0.014549,0.00006173637,0.00002344972,0.00001979878,0.0002286453,0.00003755559,0.002736856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009964007,"threshold_uncertainty_score":0.00333333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02456165493564793,"score_gpt":0.2915474947032409,"score_spread":0.266985839767593,"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."}}