{"id":"W2144436220","doi":"","title":"Horses at Work: Harnessing Power in Industrial America (review)","year":2010,"lang":"en","type":"article","venue":"Labour / Le Travail","topic":"Political Economy and Marxism","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Work (physics); Power (physics); Engineering; Mechanical engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005781292,0.000107589,0.0002377218,0.00004275672,0.0002090871,0.0000480817,0.0002526396,0.0001795464,0.002804019],"category_scores_gemma":[0.0005426898,0.0001059775,0.0000635804,0.0003252987,0.000460283,0.0001981913,0.0000512417,0.0004300614,0.0003623686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005895908,"about_ca_system_score_gemma":0.0002853727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004939861,"about_ca_topic_score_gemma":0.004905156,"domain_scores_codex":[0.9986902,0.0001669334,0.0002372544,0.0002215228,0.0001565747,0.00052745],"domain_scores_gemma":[0.9993737,0.0001403158,0.00007108035,0.0001716472,0.0000286578,0.0002145726],"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":[0.00008136769,0.0004900232,0.02953466,0.00008263907,0.00003785189,0.00006688453,0.009540561,0.000001660443,0.0007082273,0.278793,0.08519196,0.5954711],"study_design_scores_gemma":[0.0003043052,0.00001014361,0.01301038,0.00008502724,0.000004896103,6.658132e-7,0.000397834,4.156491e-7,0.00006187525,0.0007565349,0.9852076,0.0001602851],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8148807,0.001583706,0.000007978218,0.008878085,0.001031728,0.0002377442,0.00001034166,0.00007686378,0.1732929],"genre_scores_gemma":[0.9767053,0.0008433344,0.0001011219,0.003122105,0.0003873001,0.00002105713,0.000002841819,0.00001128834,0.01880573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9000157,"threshold_uncertainty_score":0.9981076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0272438114346424,"score_gpt":0.2824142328459782,"score_spread":0.2551704214113358,"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."}}