{"id":"W6960521399","doi":"10.1371/journal.pone.0300345.t007","title":"Regression results after excluding some samples.","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Plant Pathogens and Resistance","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Fertility; Livelihood; Promotion (chess); Human capital; Public policy; Quarter (Canadian coin); Survey data collection","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0257053,0.003250745,0.002794203,0.004991682,0.002358431,0.002835708,0.004266739,0.001950974,0.0702168],"category_scores_gemma":[0.08931317,0.001235567,0.00619807,0.009170762,0.001349606,0.004651992,0.003481821,0.009707102,0.02147151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753167,"about_ca_system_score_gemma":0.005128561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02908205,"about_ca_topic_score_gemma":0.01664149,"domain_scores_codex":[0.9653692,0.01558339,0.003248201,0.008914905,0.00379831,0.003086011],"domain_scores_gemma":[0.9396463,0.03949596,0.004859271,0.007968523,0.00710452,0.0009253456],"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":[0.00165887,0.001559937,0.2576911,0.003709406,0.00951092,0.002567651,0.003028882,0.004639198,0.001305089,0.01588738,0.5581478,0.1402937],"study_design_scores_gemma":[0.001082122,0.001639186,0.4062997,0.002767315,0.005432702,0.002032713,0.01497586,0.05099291,0.00357262,0.01444999,0.4963191,0.000435789],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.297058,0.008975642,0.1444392,0.007219901,0.01981214,0.01087574,0.3868313,0.01364697,0.1111412],"genre_scores_gemma":[0.7152008,0.002382486,0.05769911,0.003738651,0.00144207,0.01807557,0.1347276,0.00470118,0.06203245],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9297832,"threshold_uncertainty_score":0.2348986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06191357043897589,"score_gpt":0.2555882347975869,"score_spread":0.193674664358611,"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."}}