{"id":"W6885776903","doi":"10.1371/journal.pone.0238521.g002","title":"Examples of individual growth trajectories from healthy dogs plotted onto the growth curves.","year":2020,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Growth curve (statistics); Breed; Labrador Retriever; Body weight; Growth model; Animal model","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003776446,0.0004754723,0.0002664035,0.001457257,0.000288931,0.0003753439,0.0002351863,0.0004289115,0.01314616],"category_scores_gemma":[0.001081139,0.0001581708,0.0003122351,0.001286086,0.0001910394,0.0001727779,0.0005237657,0.000524159,0.003480514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002710365,"about_ca_system_score_gemma":0.0002393845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01765567,"about_ca_topic_score_gemma":0.02620809,"domain_scores_codex":[0.9998695,0.00002037116,0.000006463634,0.00003387277,0.00004395405,0.00002587279],"domain_scores_gemma":[0.9991463,0.0002033978,0.0001299913,0.00006221917,0.0003290132,0.000129101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003378163,0.0003772087,0.31616,0.0008828899,0.0003304585,0.002211982,0.003291628,0.01669512,0.05863639,0.003258474,0.1067512,0.4880264],"study_design_scores_gemma":[0.00002921953,0.0004951554,0.9324411,0.0001484496,0.00005392186,0.001420776,0.0009891719,0.01077473,0.004366353,0.0006773222,0.04853738,0.00006658594],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8250464,0.002736491,0.03555802,0.000649646,0.0002749202,0.0003222551,0.08731085,0.004268385,0.04383309],"genre_scores_gemma":[0.8675346,0.001772847,0.0460695,0.0001180954,0.00003867441,0.0003468219,0.05158497,0.0007721907,0.03176231],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01765567,"threshold_uncertainty_score":0.04397827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08159829835773949,"score_gpt":0.2795515892667137,"score_spread":0.1979532909089742,"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."}}