{"id":"W6939803257","doi":"10.6084/m9.figshare.26085685","title":"SFile S1: Ordinal logistic regression determining factors associated with calves’ transporting area dirtiness","year":2024,"lang":"en","type":"other","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logistic regression; Regression analysis; Ordered logit; Statistical analysis; Linear regression","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":[0.0016711,0.001415201,0.0006541075,0.001945952,0.001143642,0.0009627705,0.001825469,0.0009525829,0.08586895],"category_scores_gemma":[0.01107187,0.0003183147,0.001428573,0.002122559,0.0004183626,0.0007796776,0.001043255,0.00144137,0.004929584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002815169,"about_ca_system_score_gemma":0.006878078,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7051045,"about_ca_topic_score_gemma":0.7293187,"domain_scores_codex":[0.9991269,0.000177199,0.00008289586,0.0001341668,0.0001460388,0.0003329025],"domain_scores_gemma":[0.9941704,0.002495275,0.0008236236,0.000371475,0.001485218,0.0006539921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006327499,0.0002007818,0.8936819,0.0001661608,0.0005417909,0.0002003128,0.0003336839,0.001082106,0.0003923094,0.0004385285,0.08322892,0.01910073],"study_design_scores_gemma":[0.00009150565,0.0001706234,0.9703983,0.0001508545,0.0002193541,0.0001106228,0.001567137,0.00643594,0.0003565144,0.0002786604,0.02017199,0.0000485036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5958848,0.0004513359,0.004425377,0.001769962,0.0003443243,0.0002698403,0.3842476,0.000755671,0.01185106],"genre_scores_gemma":[0.8816364,0.0001639753,0.004176991,0.0003650477,0.0001142347,0.0006344948,0.06954299,0.0002973542,0.04306852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7051045,"threshold_uncertainty_score":0.5932643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0854516518462663,"score_gpt":0.2586004749932316,"score_spread":0.1731488231469653,"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."}}