{"id":"W2959803122","doi":"10.3390/ani9070436","title":"Development of a Scoring System to Assess Feather Damage in Canadian Laying Hen Flocks","year":2019,"lang":"en","type":"article","venue":"Animals","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Mitacs; Egg Farmers of Canada; University of Guelph","keywords":"Flock; Scoring system; Feather; Feather pecking; Benchmarking; Plumage; Reliability (semiconductor); Pecking order; Computer science; Visual inspection; Statistics; Biology; Mathematics; Ecology; Artificial intelligence; Business; Medicine; Surgery; Marketing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.005497423,0.0008372631,0.0004669101,0.004335961,0.001186571,0.0008581414,0.001553526,0.0003528373,0.002387652],"category_scores_gemma":[0.006298274,0.000494827,0.0006466582,0.001845677,0.0004959123,0.0005475665,0.001086657,0.0006671104,0.000801312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004931333,"about_ca_system_score_gemma":0.00721184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5547618,"about_ca_topic_score_gemma":0.7835032,"domain_scores_codex":[0.9967347,0.0005242206,0.0003061101,0.0003087517,0.001899352,0.000226914],"domain_scores_gemma":[0.9917135,0.0005537824,0.0006299864,0.0003327356,0.006357421,0.0004125087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006407825,0.000348044,0.3328487,0.000734866,0.0002183188,0.0002877947,0.001949237,0.007116954,0.07648931,0.00153232,0.01741488,0.5604187],"study_design_scores_gemma":[0.00008079196,0.0008758067,0.9163177,0.0002858778,0.0001651114,0.0005947482,0.001177744,0.03500085,0.01855962,0.0004543677,0.02622287,0.0002644889],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6532775,0.001216222,0.2853903,0.0006697012,0.0002775318,0.01075923,0.01057021,0.002940121,0.03489913],"genre_scores_gemma":[0.3546464,0.001126763,0.6200111,0.0001227168,0.00003641938,0.002799864,0.007375234,0.0001875919,0.01369401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4452382,"threshold_uncertainty_score":0.8957207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04689495970023604,"score_gpt":0.2530033166637901,"score_spread":0.2061083569635541,"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."}}