{"id":"W4239854429","doi":"10.5558/tfc84477-4","title":"The forestry class of 1910","year":2008,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"American Environmental and Regional History","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Forestry; Class (philosophy); Business; Geography; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0001116985,0.0001073395,0.00009479289,0.000005113081,0.0005817543,0.000002509634,0.0004987604,0.0000398135,0.0005002035],"category_scores_gemma":[0.000007663066,0.00005585854,0.00009169053,0.0001030299,0.00657596,0.00007299957,0.0002395625,0.0001524097,0.0004665958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002096557,"about_ca_system_score_gemma":0.00002611623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00035478,"about_ca_topic_score_gemma":0.0000649938,"domain_scores_codex":[0.9990465,0.00003911387,0.0001645396,0.0001575779,0.0003263923,0.0002658979],"domain_scores_gemma":[0.9993295,0.00008374926,0.0001072993,0.0004153159,0.000001836082,0.00006228738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005021255,0.0009885742,0.4280083,0.00004218823,0.0001888645,0.0001222767,0.007272501,0.03925342,0.02905023,0.00675116,0.4582657,0.02955465],"study_design_scores_gemma":[0.0004620753,0.0002135026,0.5631877,0.00001045621,0.00001851887,0.0001278131,0.0008720537,0.001653002,0.002940922,0.001707711,0.4285709,0.000235334],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.976851,0.0005935106,0.00004450746,0.0007785443,0.00009566749,0.0001233347,0.000004125146,0.00001941196,0.02148985],"genre_scores_gemma":[0.9925383,0.0002533006,0.00005202063,0.0002055349,0.00006168483,0.0000132326,0.00000189793,0.00001308469,0.006860927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1351794,"threshold_uncertainty_score":0.9961275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009940198864347091,"score_gpt":0.1975363238069986,"score_spread":0.1875961249426515,"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."}}