{"id":"W4403335593","doi":"10.3390/agriculture14101785","title":"A Multi-View Real-Time Approach for Rapid Point Cloud Acquisition and Reconstruction in Goats","year":2024,"lang":"en","type":"article","venue":"Agriculture","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Beijing Academy of Agricultural and Forestry Sciences","keywords":"Point cloud; Computer science; Cloud computing; Noise (video); Point (geometry); Data acquisition; Computer vision; Remote sensing; Extraction (chemistry); Real-time computing; Artificial intelligence; Simulation; Algorithm; Mathematics; Geography; Image (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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001257895,0.0001527889,0.000191107,0.0000414849,0.00009285715,0.00004851452,0.00004230607,0.000124509,0.00006557466],"category_scores_gemma":[0.000009068181,0.00009905682,0.00007907637,0.0001533509,0.00004066861,0.0001594217,0.00003886258,0.0001166787,0.00002179221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005269029,"about_ca_system_score_gemma":0.00000611876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000496979,"about_ca_topic_score_gemma":0.000006179859,"domain_scores_codex":[0.9992296,0.00004040193,0.0001741824,0.000324763,0.00006431209,0.000166782],"domain_scores_gemma":[0.9997942,0.00002844852,0.00002849658,0.00006868183,0.00004497929,0.00003516407],"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":[0.0006332117,0.0004403401,0.004522424,0.001861761,0.0002330637,0.0001857148,0.006387447,0.000004604869,0.8286656,0.00454383,0.04758496,0.104937],"study_design_scores_gemma":[0.002378716,0.001892473,0.9690104,0.001070837,0.0004185163,0.002894432,0.005701744,0.002431407,0.0009641735,0.0006524231,0.01130068,0.001284247],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870932,0.006393041,0.0004300002,0.0007742724,0.000416337,0.001186442,0.0001528899,0.0003313957,0.003222465],"genre_scores_gemma":[0.9928472,0.0008306186,0.005417036,0.00003101375,0.0002776712,0.0001806298,0.0001335108,0.00001427218,0.0002680282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9644879,"threshold_uncertainty_score":0.403942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246934760294843,"score_gpt":0.2929750546089028,"score_spread":0.2605057070059543,"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."}}