{"id":"W4391149359","doi":"10.1109/icacta58201.2023.10393612","title":"Petpaws: A Comprehensive Dataset and Recommender System for Canine and Feline Breeds","year":2023,"lang":"en","type":"article","venue":"","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of the Fraser Valley","funders":"","keywords":"Recommender system; Cosine similarity; Adaptability; Computer science; Selection (genetic algorithm); Breed; Collaborative filtering; Matching (statistics); Similarity (geometry); Information retrieval; Artificial intelligence; Pattern recognition (psychology); Statistics; Biology; Mathematics","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":[0.0007603079,0.001049746,0.0007316257,0.003503848,0.0007834862,0.0009699193,0.001640464,0.001849331,0.004304081],"category_scores_gemma":[0.003017188,0.0003499447,0.001077328,0.003565915,0.0002389767,0.001228795,0.000846268,0.001003091,0.004737315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008276248,"about_ca_system_score_gemma":0.001043846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04240301,"about_ca_topic_score_gemma":0.1037281,"domain_scores_codex":[0.999141,0.0001713159,0.0001057898,0.0002792555,0.0002388977,0.00006371649],"domain_scores_gemma":[0.9980875,0.0004552132,0.0001932528,0.0004992587,0.0005143902,0.0002504288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001186739,0.001224331,0.1140372,0.003136095,0.0008732765,0.00106637,0.0007175393,0.01363612,0.01466113,0.002612203,0.6882675,0.1585815],"study_design_scores_gemma":[0.0002553908,0.0006417656,0.2186467,0.000452737,0.0003520647,0.002277388,0.001236306,0.06292317,0.008328232,0.002286233,0.7022385,0.0003615553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1016059,0.002168767,0.01085621,0.0006837384,0.0003093338,0.0003550569,0.8725734,0.004628332,0.00681922],"genre_scores_gemma":[0.03940915,0.000407412,0.02354587,0.0001643965,0.00003905639,0.0002250081,0.9334466,0.0001125009,0.002649906],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04240301,"threshold_uncertainty_score":0.08431238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05335668839490058,"score_gpt":0.2599955484884615,"score_spread":0.2066388600935609,"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."}}