{"id":"W6923594476","doi":"10.14288/1.0007705","title":"Shipyards at Vancouver, April","year":2002,"lang":"en","type":"other","venue":"Open Collections","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Shipyard; Product (mathematics); Government (linguistics); Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006539013,0.00107735,0.0005166893,0.00195239,0.008994997,0.006809547,0.0010818,0.001676424,0.3956112],"category_scores_gemma":[0.001522236,0.0005267042,0.0004764493,0.002975154,0.0008206884,0.001760206,0.001849633,0.001858016,0.1423494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005399361,"about_ca_system_score_gemma":0.007487069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4543543,"about_ca_topic_score_gemma":0.8591323,"domain_scores_codex":[0.9994726,0.0000345038,0.00001531519,0.00008346573,0.0002607293,0.0001333776],"domain_scores_gemma":[0.9989007,0.00005507238,0.00002317352,0.00006544418,0.0006100036,0.0003455789],"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":[0.00008504435,0.00003355474,0.0006921389,0.00005483131,0.000006529708,0.0001826123,0.0001998509,0.0001374686,0.0001322789,0.001584599,0.9636881,0.03320291],"study_design_scores_gemma":[0.000006017518,0.000005690516,0.002142068,0.00003453387,0.000003643671,0.00002735306,0.0003775719,0.00005574237,0.0001137125,0.0002773958,0.9969503,0.00000602044],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004722548,0.002996922,0.0004499939,0.003098214,0.002572438,0.0001111216,0.010242,0.0007239661,0.9750828],"genre_scores_gemma":[0.001624959,0.0002928432,0.0001019411,0.000083548,0.0000408085,0.000006320927,0.000786857,0.00008821591,0.9969746],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5456457,"threshold_uncertainty_score":0.9034193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1588622669866623,"score_gpt":0.4093377597844466,"score_spread":0.2504754927977844,"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."}}