{"id":"W3207090612","doi":"10.29173/cons29467","title":"Sherman's March to the Sea: A March in Brilliance","year":2021,"lang":"en","type":"article","venue":"Constellations","topic":"Military History and Strategy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Political science; Law; Order (exchange); Cold war; History; Politics; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013351,0.0002545869,0.0001809437,0.0003867508,0.009965498,0.004642514,0.0003821932,0.001591072,0.005431297],"category_scores_gemma":[0.002528019,0.0002515698,0.0001263379,0.0007016787,0.006728009,0.002468072,0.002787753,0.004943823,0.0008113613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004189901,"about_ca_system_score_gemma":0.003001472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.018902,"about_ca_topic_score_gemma":0.05577447,"domain_scores_codex":[0.9991174,0.0003282631,0.00001568983,0.0000770991,0.0001872316,0.0002741993],"domain_scores_gemma":[0.9994847,0.0001462295,0.00008533397,0.00002580122,0.00008069378,0.0001773269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009944763,0.00003828363,0.002279232,0.00006876413,0.000009178068,0.0007485916,0.09643421,0.0001107117,0.0005186549,0.4969119,0.3645492,0.03823182],"study_design_scores_gemma":[0.000006608619,0.00002752554,0.002326573,0.00009648733,0.000002061036,0.0001461626,0.01866753,0.00004852798,0.0001428597,0.007947993,0.9705769,0.00001068995],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2433221,0.01805895,0.001640122,0.2448394,0.008347494,0.00003140168,0.0001756927,0.0001043148,0.4834805],"genre_scores_gemma":[0.8393586,0.004550736,0.0005497767,0.01887054,0.001386527,0.00001981686,0.00005748594,0.0001098752,0.1350967],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.018902,"threshold_uncertainty_score":0.03758395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04662551191498034,"score_gpt":0.3266839746594274,"score_spread":0.2800584627444471,"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."}}