{"id":"W2196401151","doi":"10.29173/alr287","title":"Collateral Benefits Revisited: A Case Comment on IBM Canada Limited v. Waterman","year":2015,"lang":"en","type":"article","venue":"Alberta Law Review","topic":"Business Law and Ethics","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Collateral; IBM; Collateral damage; Economics; Business; Finance; Sociology; Nanotechnology; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004447562,0.0003173458,0.0005160717,0.00004360953,0.0002360139,0.0002070151,0.0002725385,0.00008411315,0.0003053813],"category_scores_gemma":[0.0001291113,0.0002471977,0.00008606053,0.0004492147,0.00004212493,0.0004763506,0.0001857672,0.0002165407,0.0007453595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000111185,"about_ca_system_score_gemma":0.0000971062,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8933129,"about_ca_topic_score_gemma":0.7889602,"domain_scores_codex":[0.9983389,0.00003589561,0.0004749446,0.0003499363,0.0003916109,0.0004087421],"domain_scores_gemma":[0.9987161,0.0001033273,0.000218124,0.0005637578,0.0003299121,0.00006879625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003037901,0.00009527752,0.0004675556,0.004815201,0.0000652589,0.000855542,0.00002198524,0.00005001119,5.492656e-7,0.2907769,0.6962461,0.00657521],"study_design_scores_gemma":[0.0004140136,0.00001108298,0.00003445323,0.003187312,0.000164924,0.0001188502,0.000005227305,0.0001562467,0.000004046527,0.0001161524,0.9954463,0.000341395],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0670781,0.05208272,0.00000383511,0.3875628,0.002962201,0.00341046,0.00004385698,0.0002716437,0.4865844],"genre_scores_gemma":[0.5745451,0.001916362,0.00001824935,0.4217164,0.0006914785,0.0000564462,0.0002777077,0.00005964134,0.0007185698],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.507467,"threshold_uncertainty_score":0.999998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05037109296424565,"score_gpt":0.2510105469478715,"score_spread":0.2006394539836259,"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."}}