{"id":"W4392721489","doi":"10.16995/intransition.15439","title":"Cutting Across Time: Oblique Editing in <i>Arrival</i>","year":2023,"lang":"en","type":"article","venue":"[in]Transition","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bishop's University","funders":"","keywords":"Oblique case; Arrival time; Computer science; Engineering; Transport engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001304109,0.0004208373,0.0001317947,0.0006050487,0.003981092,0.007660468,0.0007012181,0.001152394,0.0106315],"category_scores_gemma":[0.00478593,0.0002135615,0.0002933605,0.0005020538,0.006610791,0.004378115,0.002003889,0.003161771,0.001475428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001982257,"about_ca_system_score_gemma":0.001230075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006088783,"about_ca_topic_score_gemma":0.01210647,"domain_scores_codex":[0.9990066,0.0005009019,0.00002785141,0.0001330533,0.0002129712,0.0001187022],"domain_scores_gemma":[0.9979734,0.001128221,0.0001532022,0.0003083287,0.0002629419,0.000173931],"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":[0.00009545984,0.00004077504,0.0005698997,0.0001073957,0.00000876662,0.0004542549,0.09777229,0.0002916466,0.003881869,0.8242177,0.03271952,0.03984049],"study_design_scores_gemma":[0.00003145711,0.00006265852,0.001489137,0.0001693069,0.00003623399,0.0005945609,0.03864031,0.001867529,0.00943361,0.05112745,0.8964992,0.00004860941],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08150123,0.001054184,0.05680429,0.01056325,0.002077781,0.0000918092,0.0001370625,0.0005586133,0.8472118],"genre_scores_gemma":[0.8717895,0.0008253834,0.01515319,0.001524662,0.000481793,0.00006019085,0.00008353971,0.0007084675,0.1093733],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0106315,"threshold_uncertainty_score":0.03556591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02871411319128281,"score_gpt":0.2450957503520772,"score_spread":0.2163816371607944,"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."}}