{"id":"W4409329295","doi":"10.3390/agriculture15080814","title":"A Machine Learning-Based Method for Pig Weight Estimation and the PIGRGB-Weight Dataset","year":2025,"lang":"en","type":"article","venue":"Agriculture","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Science and Technology Major Project; Beijing Academy of Agricultural and Forestry Sciences","keywords":"Estimation; Weight estimation; Artificial intelligence; Machine learning; Statistics; Computer science; Mathematics; Engineering","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":[0.0009266333,0.002088655,0.0008143857,0.002161237,0.0004484816,0.0008506982,0.001848574,0.001735644,0.005119249],"category_scores_gemma":[0.00212475,0.0003858331,0.001098944,0.002078702,0.0003522398,0.0007862808,0.001191703,0.001187122,0.005639702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006656868,"about_ca_system_score_gemma":0.0008351599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008267754,"about_ca_topic_score_gemma":0.01596203,"domain_scores_codex":[0.999217,0.00008528695,0.00006767077,0.0003109431,0.0002494472,0.00006967486],"domain_scores_gemma":[0.9995266,0.00006632677,0.00006331577,0.0001388984,0.0001727565,0.00003211295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001141883,0.001206903,0.02720632,0.001333311,0.0005919058,0.0007080756,0.0001016263,0.03224687,0.03676435,0.00259721,0.2600662,0.6360354],"study_design_scores_gemma":[0.0003841413,0.0008582807,0.08424518,0.0003916308,0.0002323555,0.001976262,0.0002315691,0.6737434,0.04160886,0.006992959,0.1890693,0.0002660684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2092677,0.004494469,0.4426001,0.001077713,0.001654904,0.001739343,0.2619856,0.05732738,0.01985282],"genre_scores_gemma":[0.1618587,0.001031689,0.3215929,0.0005012506,0.000145993,0.00203569,0.4994074,0.001267298,0.0121591],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008267754,"threshold_uncertainty_score":0.01712555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01873972489615876,"score_gpt":0.3276596693161173,"score_spread":0.3089199444199586,"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."}}