{"id":"W6960785633","doi":"10.1371/journal.pone.0292336.t002","title":"Respondent characteristics.","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Respondent; Cannabis; Latent class model; Multinomial logistic regression; Product (mathematics); Preference; Consumption (sociology); Class (philosophy)","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":["insufficient_payload"],"category_scores_codex":[0.002546792,0.000612587,0.0005777978,0.00196727,0.00103652,0.001529847,0.001050987,0.0010334,0.3735904],"category_scores_gemma":[0.0164135,0.0003192097,0.0005911154,0.004748451,0.0002083069,0.001261033,0.001608228,0.001673713,0.149412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709918,"about_ca_system_score_gemma":0.002792136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01061226,"about_ca_topic_score_gemma":0.008490392,"domain_scores_codex":[0.996927,0.0009005976,0.0003633495,0.0004565023,0.0008063887,0.0005462567],"domain_scores_gemma":[0.9941357,0.001517975,0.000505209,0.0006084716,0.002728268,0.0005043673],"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":[0.0004064431,0.0004347512,0.03815798,0.001132129,0.00003153547,0.0001156802,0.002520314,0.0002717344,0.0002716897,0.00753191,0.749155,0.1999709],"study_design_scores_gemma":[0.00008973233,0.0001524824,0.05216506,0.0005876991,0.00002123796,0.0001608659,0.004025215,0.0003730514,0.0001957504,0.002019177,0.9401734,0.00003621616],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05015424,0.001469132,0.005225742,0.004989447,0.001364385,0.00606576,0.5140468,0.0008777691,0.4158067],"genre_scores_gemma":[0.1765575,0.0041435,0.01566923,0.008192266,0.0006558121,0.03943319,0.2832401,0.0009227567,0.4711857],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6264096,"threshold_uncertainty_score":0.8934972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03616555623184511,"score_gpt":0.2477982120959276,"score_spread":0.2116326558640825,"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."}}