{"id":"W4410090255","doi":"10.26443/law.v69i4.1708","title":"Thesis Survey","year":2024,"lang":"en","type":"article","venue":"McGill Law Journal","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002926529,0.00007666021,0.00009840577,0.00004964157,0.004081404,0.0003868011,0.0003014842,0.00007810291,0.00241113],"category_scores_gemma":[0.0003592288,0.00006394227,0.00009930496,0.000294157,0.0003367038,0.000401373,0.00002621397,0.000296655,0.001115287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001461903,"about_ca_system_score_gemma":0.00003030971,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01834054,"about_ca_topic_score_gemma":0.1782802,"domain_scores_codex":[0.9984379,0.0004446896,0.0002248674,0.0001385592,0.00042208,0.0003319223],"domain_scores_gemma":[0.9990649,0.000500528,0.00003564097,0.00009361217,0.0001277316,0.0001775593],"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":[0.000005709732,0.00001553919,0.0002364703,0.000002340528,0.0000204142,0.000075002,0.001071231,0.00001385498,0.00002108834,0.9553966,0.002177449,0.04096431],"study_design_scores_gemma":[0.000009038281,0.00001575105,0.0001540619,0.00002971784,0.000007934033,0.00001791578,0.0007207808,0.00004445926,0.0005907996,0.01531978,0.9829953,0.00009440287],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006862367,0.0004491005,0.0004475148,0.002419475,0.003247785,0.00008012877,0.000031984,0.0001655765,0.9862961],"genre_scores_gemma":[0.997432,0.0001887248,0.0001849489,0.0002058601,0.0007107789,0.000001650436,6.559192e-7,0.00001479623,0.001260567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9905697,"threshold_uncertainty_score":0.9996625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1241855439824782,"score_gpt":0.3967832414877197,"score_spread":0.2725976975052415,"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."}}