{"id":"W2596436454","doi":"10.1007/s00359-017-1156-x","title":"Multispectral images of flowers reveal the adaptive significance of using long-wavelength-sensitive receptors for edge detection in bees","year":2017,"lang":"en","type":"article","venue":"Journal of Comparative Physiology A","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"European Social Fund; Human Frontier Science Program; National Science Foundation","keywords":"Multispectral image; Trichromacy; Biology; Segmentation; Receptor; Wavelength; Pollination; Artificial intelligence; Computer vision; Biological system; Botany; Computer science; Color vision; Optics; Physics; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002421708,0.00009701159,0.0004254114,0.00001541112,0.0002312018,0.000007374486,0.0001898849,0.00004270405,0.000003705716],"category_scores_gemma":[0.00007831231,0.00003477865,0.0001367544,0.000058308,0.0003994734,0.0001274478,0.00003443521,0.0001416785,2.829314e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002139935,"about_ca_system_score_gemma":0.00001107741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001217437,"about_ca_topic_score_gemma":0.001110008,"domain_scores_codex":[0.9992493,0.0001357795,0.0002998138,0.00009993849,0.00008040369,0.0001347791],"domain_scores_gemma":[0.9983113,0.0005520539,0.0008390904,0.00002205114,0.0002556066,0.0000199113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001169793,0.00006323666,0.002795904,0.000004723353,0.00006972543,0.000001263791,0.0006056416,0.00006556626,0.9933474,0.00002803154,0.00005644206,0.001792243],"study_design_scores_gemma":[0.0002199291,0.0007344973,0.6976787,0.00005453202,0.00001721028,0.000004688944,0.001485322,0.0003339533,0.2990644,0.00032732,0.00002314386,0.00005629099],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993284,0.0001391432,0.00004048687,0.0001267618,0.0001120217,0.0001666621,0.00003636894,0.000001395208,0.00004873797],"genre_scores_gemma":[0.9995189,0.00005195815,0.0002170223,0.00000769621,0.0001902798,0.000002737465,7.192828e-7,4.827938e-7,0.00001015999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6948828,"threshold_uncertainty_score":0.1778241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088823099840185,"score_gpt":0.3037768519909596,"score_spread":0.1948945420069411,"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."}}