Marillion, Montreal & Leonard Cohen essays, interviews & photos : (teilweise zweisprachig/partially bilingual, Deutsch/Englisch - German/English) : 1934-2024: 90. Jahrestag Leonard Cohen : a lil' bilingual Leonard Cohen Montreal city guide, Engl./Deutsch
Bibliographic record
Abstract
Approach #Maybe #Montreal #The first idea #Not just one book #Pre-sounds #Phone call #Prog & Rock #Rock & Poetry #Essence I. Book Of Marillion I.I.Timeline & Milestones of Marillion LLL Talking with Fish (2014) "Ich bin nach wie vor ich selbst"/ "I am still the same as before" I.I.II .Weltschmerz -Ein Werk im Geist der Zeit (2020) Ex-Marillion-Sänger "Fish" veröffentlicht (s)ein "Masterpiece"/ Fish releases a / his "Masterpiece" LLIIL Talking with Steve "H" Hogarth (2022) Uber die Reflektion des Zeitgeistes/ About the reflection of the zeitgeist I.I.I V. Marillion spricht über/ talking on Leonard Cohen in Montreal 2022 "I wonder what it's all about" -Montreal Marillion Weekend 2022 I.I.V. Talking with Steve Rothery (2022) "Marillion ist ein großes Buch mit vielen Kapiteln"/ "Marillion is a big book with many chapters" I.I.VI.From Montreal To Stuttgart (2022) -Deutschland-Tourstart -"This Song is dedicated to Leonard Cohen" I.I.V.II."H-Neutral"-concerts in 2022 "Famous Blue Raincoat" live in Concert by Steve Hogarth I.I.V.III.From Stuttgart to Montreal (2023) -Drei Nächte in Montreal/ Marillion Weekend -Three Nights in Montreal I.I.I X.First We Took Montreal, Then We Took Berlin (2023) -oder/ or "Seasons End in Berlin -Das erste deutsche Marillion Weekend/ The first Marillion Weekend in Germany I.I.X.More Live -Activities in 2023 -From "The End Of The Tunnel" 'til "The Tour Before It's X-Mas" I.II.From "Famous Blue Raincoat" to "The Crow And The Nightingale" -Ein Unbeantworteter Brief/ An Unanswered Letter I.III.Marillion Live Locations in Montreal 1983-2023 Knapp 40 Konzerte in 40 Montreal-Jahren/ Almost 40 gigs in 40 years
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".