{"id":"W3122567227","doi":"10.1007/978-3-030-62666-2_4","title":"Case Study – Methods","year":2021,"lang":"en","type":"book-chapter","venue":"SpringerBriefs in environmental science","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Calculator; Ecological footprint; Footprint; Sampling (signal processing); Geography; Environmental resource management; Computer science; Environmental science; Ecology; Sustainability; Archaeology; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002671681,0.000783851,0.0006940877,0.0002063644,0.000523912,0.0001446525,0.001055189,0.0002943742,0.01980164],"category_scores_gemma":[0.00008433458,0.0008149392,0.0002187128,0.0002845807,0.003975391,0.0007163998,0.00364803,0.0009883232,0.0007093351],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00506223,"about_ca_system_score_gemma":0.00007503144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008318616,"about_ca_topic_score_gemma":0.0005112182,"domain_scores_codex":[0.9943164,0.0001516238,0.0008268051,0.002135317,0.00149585,0.001074014],"domain_scores_gemma":[0.9974193,0.000105012,0.0002770683,0.001654753,0.000003370856,0.0005404867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008726845,0.004930109,0.47392,0.00008976659,0.0001320278,0.1233676,0.01075882,0.002024614,0.02917974,0.002683883,0.0002819994,0.3525442],"study_design_scores_gemma":[0.006836735,0.003484817,0.5475734,0.0003996506,0.0007297673,0.03055728,0.03877398,0.001619742,0.01402305,0.01590825,0.3258631,0.0142302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6239306,0.0002264896,0.00006545668,0.00002811685,0.0003154837,0.001187054,0.00001500109,0.00005127992,0.3741805],"genre_scores_gemma":[0.8253979,0.0000997719,0.005222027,0.0001740252,0.00005674591,0.00004929713,0.000007069962,0.00009698515,0.1688962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.338314,"threshold_uncertainty_score":0.9994301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02140330918065819,"score_gpt":0.3050903646594501,"score_spread":0.2836870554787919,"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."}}